Ladle wall erosion monitoring method and device in ladle argon blowing process and electronic equipment

Abstract

The invention relates to the technical field of ladle argon blowing, in particular to a ladle wall erosion monitoring method and device for a ladle argon blowing process and electronic equipment. The method comprises the following steps: acquiring a real vibration acceleration signal of a ladle wall in a ladle argon blowing process; extracting a specific vibration amplitude of the real vibration acceleration signal; substituting the specific vibration amplitude into a pre-established linear correlation model of the specific vibration amplitude and a Young modulus, and reversely deducing an actual Young modulus; and determining the erosion degree of the ladle wall based on the actual Young modulus. The vibration signal is used as an indirect index, direct contact with a high-temperature environment is not needed, and reliable backstepping of the ladle wall erosion degree is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ladle argon blowing, and particularly relates to a ladle argon blowing process ladle wall erosion monitoring method and device and electronic equipment. BACKGROUND

[0002] Ladle bottom argon blowing is a core refining technology in the modern steelmaking process. By blowing inert argon into the ladle bottom, the stirring, purification and temperature homogenization of the molten steel can be achieved, which directly affects the cleanliness, production efficiency and cost control of the steel. However, the temperature of the molten steel in the ladle is as high as 1700°C or above, and the refractory lining in the ladle wall is subjected to long-term chemical erosion, mechanical scouring and corrosion by slag under high temperature molten steel, which is prone to spalling or excessive erosion. Spalled refractory particles can enter the molten steel to form non-metallic inclusions, reducing the quality of the steel; and severe erosion can cause the ladle to leak, causing production interruption and safety accidents.

[0003] At present, the monitoring method of ladle wall erosion has obvious limitations: on the one hand, the high temperature and high corrosive environment makes it difficult for most physical sensors (such as thermocouples and pressure sensors) to work stably for a long time, and it is difficult to directly obtain the internal state data of the ladle wall; on the other hand, existing researches mainly focus on the influence of argon blowing parameters (such as flow rate and time) on the removal of molten steel inclusions, or analyze the flow field characteristics of molten steel through numerical simulation, and cannot infer the degree of ladle wall erosion through monitorable physical signals.

[0004] Therefore, there is an urgent need for a ladle erosion monitoring method based on monitorable physical signals without direct contact with high temperature environment to solve the bottleneck of the prior art. SUMMARY

[0005] Therefore, the embodiments of the present application provide a ladle argon blowing process ladle wall erosion monitoring method and device and electronic equipment, which take vibration signals as an indirect index, do not need to directly contact with high temperature environment, and realize reliable backstepping of the degree of ladle wall erosion.

[0006] The first aspect of the embodiments of the present application provides a ladle argon blowing process ladle wall erosion monitoring method, comprising: collecting a real vibration acceleration signal of the ladle wall in the ladle argon blowing process; extracting a specific vibration amplitude of the real vibration acceleration signal; substituting the specific vibration amplitude into a pre-established linear correlation model of the specific vibration amplitude and Young's modulus to backstep an actual Young's modulus; determining the degree of ladle wall erosion based on the actual Young's modulus.

[0007] In one embodiment, it further comprises: establishing a three-phase flow model of argon, molten steel and slag in the ladle to simulate the flow field characteristics of the bubble flow. establish a fluid-structure coupling model coupled with the three-phase flow model, and use Young's modulus to represent the erosion degree of the ladle wall; simulate the bubble flow rising flow field characteristics using the fluid-structure coupling model to obtain vibration acceleration data corresponding to different Young's moduli; extract specific vibration amplitudes of the vibration acceleration data corresponding to different Young's moduli; fit a linear correlation model of the specific vibration amplitudes and Young's moduli based on the correspondence between the specific vibration amplitudes and the Young's moduli.

[0008] In one embodiment, the three-phase flow model uses Realizable The two-equation model describes the turbulent flow characteristics of the molten steel, and the VOF method is used to capture the three-phase interface. The control equations of the three-phase flow model include continuity equation, momentum conservation equation, turbulent kinetic energy k equation and turbulent dissipation rate ε equation.

[0009] In one embodiment, after collecting the real vibration acceleration signal of the ladle wall during the ladle argon blowing process, the method further comprises: wavelet threshold denoising is performed on the real vibration acceleration signal; perform continuous wavelet transform time-frequency analysis on the denoised signal, and extract specific vibration amplitudes from the time-frequency analysis results.

[0010] In one embodiment, the wavelet threshold denoising comprises: using a hard threshold function to filter noise; wherein the threshold of the hard threshold function is determined by unbiased likelihood estimation.

[0011] In one embodiment, the specific vibration amplitude is the vibration amplitude of the characteristic frequency generated when the bubble flow initially impacts the ladle wall.

[0012] In one embodiment, the erosion degree of the ladle wall is determined based on the actual Young's modulus, including determining the erosion degree of the ladle wall based on the degree of decrease of the actual Young's modulus compared with the initial Young's modulus, specifically comprising: when the degree of decrease of the actual Young's modulus compared with the initial Young's modulus is in the range of 5% to 10%, it is determined as slight erosion; when the degree of decrease of the actual Young's modulus compared with the initial Young's modulus is in the range of 10% to 20%, it is determined as moderate erosion; when the degree of decrease of the actual Young's modulus compared with the initial Young's modulus exceeds 20%, it is determined as severe erosion.

[0013] In one embodiment, the collection of the real vibration acceleration signal is realized by a vibration sensor installed on the outside of the ladle wall.

[0014] The second aspect of the embodiment of the present application provides a ladle argon blowing process ladle wall erosion monitoring device, comprising: The acquisition module is configured to acquire a real vibration acceleration signal of the ladle wall in the ladle argon blowing process. The feature extraction module is configured to extract a specific vibration amplitude of the real vibration acceleration signal. The Young's modulus determination module is configured to substitute the specific vibration amplitude into a pre-established linear correlation model of the specific vibration amplitude and the Young's modulus to back-calculate an actual Young's modulus. The erosion determination module is configured to determine a ladle wall erosion degree based on the actual Young's modulus.

[0015] The third aspect of the embodiment of the present application provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to enable the electronic device to implement the ladle argon blowing process ladle wall erosion monitoring method provided by the first aspect of the embodiment of the present application.

[0016] The fourth aspect of the embodiment of the present application provides a computer program product comprising a computer program, wherein the computer program is executed to enable the method provided by the first aspect of the embodiment of the present application to be performed.

[0017] The ladle argon blowing process ladle wall erosion monitoring method provided by the first aspect of the embodiment of the present application comprises the following steps: acquiring a real vibration acceleration signal of the ladle wall in the ladon argon blowing process; extracting a specific vibration amplitude of the real vibration acceleration signal; substituting the specific vibration amplitude into a pre-established linear correlation model of the specific vibration amplitude and the Young's modulus to back-calculate an actual Young's modulus; and determining a ladle wall erosion degree based on the actual Young's modulus. Based on the actually monitored vibration amplitude, the Young's modulus is back-calculated through the linear model to determine the ladle wall erosion degree, thereby realizing indirect real-time monitoring of the ladle erosion in a high-temperature environment, providing theoretical support for adjusting the argon blowing parameters, predicting the ladle life, ensuring the steelmaking safety and steel quality. The direct contact with the high-temperature corrosion environment in the ladle is avoided, thereby solving the bottleneck of the physical sensor failure. The vibration signal is used as an indirect index, the erosion state is monitored in real time and in a non-invasive manner through simple linear relationship conversion, the equipment cost is reduced, the monitoring reliability and safety are improved, and sustainable technical support is provided for the ladle life management.

[0018] It can be understood that the beneficial effects of the second aspect to the fourth aspect can be referred to the related description in the first aspect, which will not be repeated here. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0020] Figure 1 is a flowchart of a method for monitoring ladle wall erosion in a ladle argon blowing process provided by an embodiment of the present application; Figure 2 is a multiphase flow streamline diagram of the ladle argon blowing process; Figure 3 is a ladle wall vibration acceleration curve; Figure 4 is a Morlet wavelet transform time-frequency diagram; Figure 5 is a continuous wavelet transform coefficient diagram; Figure 6 is a comparison of bubble flow patterns between a water model and numerical simulation (a is a water model, and b is a fluid-structure coupling simulation); Figure 7 is an alignment diagram of the ladle wall vibration curve and the bubble flow velocity curve; Figure 8 is a vibration amplitude and Young's modulus scatter diagram and a linear fitting line; Figure 9 is a structural schematic diagram of a device for monitoring ladle wall erosion in a ladle argon blowing process provided by an embodiment of the present application; Figure 10 is a structural schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0021] In the following description, specific details are set forth in order to provide a thorough understanding of embodiments of the present application. However, persons skilled in the art will understand that the present application can be practiced without these specific details, in other instances, well-known systems, structures, circuits, and methods have not been described in detail in order to not obscure the understanding of this application.

[0022] It should be understood that when used in the specification and the appended claims of the present application, the term "comprising" indicates the presence of the described features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0023] It should also be understood that the term “and / or” as used herein, means any one or more of the associated listed items, and includes combinations of one or more of the associated listed items. Also, it is to be understood that the use of a singular term, such as, for example, “a”, “an”,”“the”, and / or “said” in the specification and / or claims can include the equivalent plural forms.

[0024] As used in the description of the application and the appended claims, the term “if’ can be interpreted to mean “when” or “upon” or “in response to determining” or “in response to detecting” depending on the context. Similarly, the phrase “if it is determined” or “if [a described condition or event] is detected” can be interpreted to mean “upon determining” or “in response to determining” or “upon [the described condition or event] being detected” or “in response to [the described condition or event] being detected”, depending on the context.

[0025] In addition, the terms “first”, “second”, “third”, etc. as used in the description of embodiments herein and in the claims (if any) are only used to differentiate one element from another, and cannot be understood as indicating or implying relative importance.

[0026] Reference throughout this specification to “one embodiment” or “an embodiment” or “some embodiments” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the application. Thus, the appearances of the phrases “in one embodiment”, “in some embodiments”, “in other embodiments”, “in additional embodiments”, and so on, in various places throughout this specification are not necessarily all referring to the same embodiment, unless otherwise specified. The terms “comprise”, “comprising”, “have”, “having”, “include”, “including”, and “contain”, “containing” as used throughout this specification, mean “including but not limited to” unless otherwise expressly specified and / or indicated by context. Accordingly, the description herein makes reference to various embodiments of the application and alternative embodiments.

[0027] As shown in Figure 1 The ladle argon blowing process wall erosion monitoring method provided by the embodiments of the application includes the following steps S101 to S104: Step S101, collecting a real vibration acceleration signal of a ladle wall in a ladle argon blowing process; Step S102, extracting a specific vibration amplitude of the real vibration acceleration signal; Step S103, substituting the specific vibration amplitude into a pre-established linear correlation model of the specific vibration amplitude and Young's modulus to back-calculate an actual Young's modulus; Step S104, determining a ladle wall erosion degree based on the actual Young's modulus.

[0028] In the application, the method collects the real vibration acceleration signal in the argon blowing process through the vibration sensor installed on the outside of the ladle wall, then digitizes the signal to extract the vibration amplitude parameter, inputs the amplitude into the pre-established linear correlation model to back-propagate the actual Young's modulus of the ladle wall refractory, and determines the erosion degree based on the comparison of the Young's modulus and the initial value. For the collected signal, the piezoelectric accelerometer can be used to continuously record the data at a sampling frequency of not less than 81.25 Hz, and for the extraction of the amplitude, the root mean square value can be calculated through time domain analysis or the specific frequency component can be focused on through frequency domain analysis. In step S101, the real vibration acceleration signal collected in the ladle argon blowing process is the horn type amplitude signal within 1s from the start of the ladle argon blowing.

[0029] Among them, for the real vibration acceleration signal collected in step S102, wavelet threshold denoising, Morlet continuous wavelet transform, and extraction of specific vibration amplitude of the real vibration acceleration signal are sequentially performed, for example, the actual vibration amplitude corresponding to the scale 2.

[0030] The embodiment of the application realizes the indirect real-time monitoring of the ladle erosion in the high-temperature environment by back-propagating the Young's modulus through the linear model based on the actually monitored vibration amplitude, judging the ladle wall erosion degree, and providing theoretical support for adjusting the argon blowing parameters, predicting the ladle life, and ensuring the safety of steelmaking and the quality of steel. The bottleneck of the physical sensor failure is avoided by avoiding direct contact with the high-temperature corrosion environment inside the ladle, thereby realizing real-time and non-invasive monitoring of the erosion state through simple linear relationship conversion, reducing the equipment cost, improving the reliability and safety of the monitoring, and providing sustainable technical support for the ladle life management.

[0031] In one embodiment, it further comprises: A three-phase flow model of argon, molten steel and slag in the ladle is established to simulate the bubble flow rising flow field characteristics; A fluid-structure coupling model coupled with the three-phase flow model is established, and the Young's modulus is used to represent the ladle wall erosion degree; The fluid-structure coupling model is used to simulate the bubble flow rising flow field characteristics to obtain vibration acceleration data corresponding to different Young's moduli; The specific vibration amplitude of the vibration acceleration data corresponding to different Young's moduli is extracted; Based on the corresponding relationship between the specific vibration amplitude and the Young's modulus, a linear correlation model of the specific vibration amplitude and the Young's modulus is fitted.

[0032] In the application, the method further comprises establishing a three-phase flow model of argon, molten steel and slag in the ladle to simulate the flow field characteristics in the process of bubble flow rising, establishing a fluid-structure coupling model coupled with the fluid domain and simulating different erosion states by adjusting the Young's modulus parameter, generating corresponding vibration acceleration data by numerical simulation, extracting a specific vibration amplitude, and fitting a linear relationship model of the vibration amplitude and the Young's modulus based on the data. For establishing the three-phase flow model, the Realizable k-ε turbulence model and the VOF multiphase flow method can be used to realize in ANSYS Fluent, and for fitting the linear model, the least square method can be used to obtain the coefficients.

[0033] The embodiment of the application pre-fits a linear correlation model by establishing a three-phase flow model and a fluid-structure coupling model, accurately restores the physical interaction process of bubble flow and ladle wall vibration by numerical simulation, ensures the physical basis of the linear relationship, can cover various working conditions from slight to severe by simulating vibration responses under different erosion states, improves the generalization ability and prediction accuracy of the model, provides a reproducible theoretical basis for practical application, and reduces the uncertainty of relying on experimental calibration.

[0034] In one embodiment, the three-phase flow model adopts Realizable two-equation model to describe the turbulent flow characteristics of molten steel, and VOF method is used to capture the three-phase interface. The control equations of the three-phase flow model include continuity equation, momentum conservation equation, turbulent kinetic energy k equation and turbulent dissipation rate ε equation.

[0035] In the application, the three-phase flow model adopts Realizable k-ε two-equation model to describe the turbulent flow characteristics of molten steel, includes solving continuity equation, momentum conservation equation, turbulent kinetic energy k equation and turbulent dissipation rate ε equation, and uses VOF method to capture the dynamic three-phase interface. For the turbulence model, adaptive calculation parameter Cμ can be set to optimize the viscosity simulation, and for the VOF method, the volume fraction constraint can be solved by iteration to ensure the sharpness of the interface.

[0036] Specifically, taking an actual ladle as a prototype, a three-phase flow model of argon (g)-molten steel (s)-slag (sl) is constructed, Realizable k-ε two-equation model is used to describe the turbulent flow characteristics of molten steel, and VOF method is used to capture the three-phase interface (to ensure accurate calculation of sharp interface and dispersed phase distribution). two-equation model to describe the turbulent flow characteristics of molten steel, and VOF method is used to capture the three-phase interface (to ensure accurate calculation of sharp interface and dispersed phase distribution).

[0037] Model physical parameters: density of molten steel 7000 kg / m 3 , viscosity 0.0067 Pa・s; density of slag 2700 kg / m 3 , viscosity 0.2 Pa・s; density of argon 1.6228 kg / m 3Viscosity 2.125×10 -5 Pa·s; interfacial tension: molten steel - slag 1.3 N / m, slag - argon 0.5 N / m, argon - molten steel 1.82 N / m.

[0038] Governing equations include the continuity equation (describing mass conservation), the momentum conservation equation (including surface tension and gravity terms), the turbulent kinetic energy k-equation, and the dissipation rate. The equations (describing turbulence characteristics) are as follows: Continuity equation: Momentum conservation equation (NS equation): In the formula: For the velocity vector of a multiphase fluid, ; For multiphase fluid density, P represents pressure. t represents time. ; The effective viscosity coefficient, g is the gravitational acceleration vector. F is the surface tension vector, N; Turbulent kinetic energy k-equation: In the formula: the left side is Local time change rate ( ) and convective transport items ( The first item on the right is molecular viscosity (); , ) and turbulent viscosity ( Caused by diffusion term, for The Prandtl number is taken as 1.0; The turbulent kinetic energy generation term is generated by the average velocity gradient. ( (mean strain rate tensor). This is the term for turbulent kinetic energy generation caused by buoyancy; The dissipation term of turbulent kinetic energy; This is the Mach number-dependent turbulent kinetic energy dissipation term in compressible flow.

[0039] Turbulent dissipation rate equation In the formula: the left side is The local time change rate and convective transport term; the first term on the right is diffusion term of the equation (1) Prandtl number of the equation (1) (taking 1.2) generation term of the equation (1) module of the average 1 strain rate generation term of the equation (1) module of the average 1 strain rate ) dissipation term of the equation (1) dissipation term of the equation (1) influence term of the equation (1) (buoyancy on =1.44, buoyancy coefficient, which varies with the flow direction)

[0040] wherein: , adaptive calculation (related to the flow state)

[0041] Mesh and calculation settings: 0.06m mesh size, total mesh number≥110 million; calculation step 0.04s, total calculation time 12s (to ensure that the flow field reaches dynamic balance); SIMPLEC algorithm is used for flow field solution.

[0042] In application, the boundary conditions of the three-phase flow model are set as: The initial molten steel depth in the ladle is 3.15m, the slag thickness is 0.1m, and the initial temperature is 1973K; Argon blowing adopts DPM argon bubble particle bottom injection into the ladle, the total argon flow rate is 0.006kg / s, and the average bubble diameter is 0.02m; The ladle wall is a non-slip wall, and a standard wall function is used. The model outlet is the upper surface of the ladle, which is a pressure outlet.

[0043] In application, the fluid domain solution of the fluid-structure coupling model is carried out in the Fluent module, the solid domain (ladle wall) solution is carried out in the transient structure (Transient structural) module, and the coupling interface data is interacted through the System coupling module; The fluid-structure coupling interface satisfies the stress, displacement, heat flow and temperature continuity, i.e. wherein subscript f represents fluid, and s represents solid.

[0044] The ladle wall is regarded as a homogeneous isotropic elastic body, and the influence of temperature on mechanical parameters is ignored; the Young's modulus of the ladle wall refractory material , wherein normal stress ​For normal strain, the erosion degree from slight to severe is simulated by changing the value of E (290-300 MPa).

[0045] The three-phase flow model of the embodiment of the application adopts Realizable k-ε model and VOF method, which can effectively describe the turbulent flow characteristics of the molten steel and capture the sharp interface of the multi-phase, avoiding the error caused by the simplified model; the Realizable k-ε model improves the authenticity of the flow field simulation by adaptively calculating the turbulent flow parameters, and the VOF method ensures the accurate calculation of the distribution of the gas-liquid-slag three-phase, thereby providing high-fidelity input data for subsequent vibration analysis and enhancing the reliability of the entire monitoring chain.

[0046] In one embodiment, after collecting the real vibration acceleration signal of the ladle wall during the ladle argon blowing process, the method further comprises: wavelet threshold denoising the real vibration acceleration signal; performing continuous wavelet transform time-frequency analysis on the denoised signal, and extracting a specific vibration amplitude from the time-frequency analysis result.

[0047] In application, after collecting the real vibration acceleration signal, the signal is subjected to wavelet threshold denoising to remove noise interference, and then the denoised signal is subjected to continuous wavelet transform time-frequency analysis, and a specific vibration amplitude is extracted from the result as a characteristic value. For wavelet threshold denoising, a threshold determination method based on unbiased likelihood estimation can be used, and for continuous wavelet transform, a Morlet mother wavelet function can be used for multi-scale decomposition.

[0048] The embodiment of the application adds the steps of wavelet threshold denoising and continuous wavelet transform time-frequency analysis before signal extraction. In view of the non-stationary characteristics of the vibration signal, wavelet denoising can effectively filter Gaussian noise, and time-frequency analysis can focus on the high-frequency components in the rising stage of the bubble flow; the limitations of traditional Fourier transform in non-stationary signals are avoided, the accuracy of vibration amplitude extraction is ensured, and the sensitivity and anti-interference ability of erosion judgment are improved.

[0049] In one embodiment, the wavelet threshold denoising comprises: filtering noise using a hard threshold function; wherein the threshold of the hard threshold function is determined by unbiased likelihood estimation.

[0050] In application, the wavelet threshold denoising process comprises filtering noise coefficients using a hard threshold function, wherein the threshold is calculated by an unbiased likelihood estimation method. For the hard threshold function, the absolute value of the wavelet coefficient is set to zero when it is less than the threshold, otherwise it is retained. For unbiased likelihood estimation, the threshold point can be determined by sorting the square of the absolute value of the signal and minimizing the risk function.

[0051] In application, the threshold is determined by using the unbiased likelihood estimation (rigrsure) wherein , is the risk function the order number of the minimum; The noise coefficients are filtered by using the hard threshold function: wherein the wavelet coefficient.

[0052] In application, the Morlet mother wavelet is used in the continuous wavelet transform time-frequency analysis, and the expression is wherein is the central angular frequency; the characteristic amplitude is the vibration amplitude corresponding to the scale 2 in the wavelet transform, and the scale corresponds to the actual frequency 40.625 Hz.

[0053] The embodiments of the application limit the wavelet threshold denoising to use the hard threshold function and the unbiased likelihood estimation to determine the threshold. The unbiased likelihood estimation can adaptively calculate the optimal threshold according to the signal characteristics, and reduce the deviation caused by subjective setting. The hard threshold function retains the effective signal mutation point when denoising, and avoids the signal distortion caused by the soft threshold function. The combination improves the robustness of the denoising process, and lays a clean data foundation for feature extraction.

[0054] In one embodiment, the specific vibration amplitude is the vibration amplitude of the characteristic frequency generated when the bubble flow initially impacts the package wall.

[0055] In application, the specific vibration amplitude corresponds to the vibration component of the characteristic frequency generated when the bubble flow initially impacts the package wall, and the frequency component is directly related to the change of the package wall stiffness. For the characteristic frequency, the frequency band near 40.625 Hz corresponding to the focusing scale 2, and for the amplitude extraction, the maximum value or the average value of the wavelet transform coefficient at the scale can be read.

[0056] In application, the vibration amplitude corresponding to the scale 2 in the wavelet transform (the scale corresponds to the high-frequency characteristics of the initial impact of the bubble flow, and is most sensitive to the erosion degree) is extracted. After obtaining the vibration amplitude corresponding to the scale 2 in the wavelet transform corresponding to different Young's moduli, a linear correlation model of the specific vibration amplitude and the Young's modulus can be obtained by linear regression analysis: ; wherein, the model parameters: a=0.5178±0.02786, b=−9.33333×10 −4 ±9.42809×10 −5 .

[0057] Model accuracy: residual sum of squares ≤8×10 -7, the correlation coefficient is less than or equal to -0.98995, and the determination coefficient is greater than or equal to 0.98 (indicating that the linear correlation is extremely strong).

[0058] The embodiment of the application clearly specifies that a specific vibration amplitude corresponds to the characteristic frequency of the initial impact of the bubble flow, and the frequency component directly reflects the instantaneous mechanical action of the bubble flow on the ladle wall, which is strongly related to the change in the stiffness of the refractory material; focusing on this characteristic frequency avoids the redundancy of full-band analysis, making the monitoring index more targeted and sensitive, thereby enabling early identification of minor erosion and preventing potential safety accidents.

[0059] In one embodiment, the determination of the erosion degree of the ladle wall based on the actual Young's modulus includes determining the erosion degree of the ladle wall based on the degree of decrease of the actual Young's modulus compared to the initial Young's modulus, specifically including: When the degree of decrease of the actual Young's modulus compared to the initial Young's modulus is in the interval of 5% to 10%, it is determined as slight erosion; When the degree of decrease of the actual Young's modulus compared to the initial Young's modulus is in the interval of 10% to 20%, it is determined as moderate erosion; When the degree of decrease of the actual Young's modulus compared to the initial Young's modulus exceeds 20%, it is determined as severe erosion.

[0060] In application, the determination of the erosion degree of the ladle wall based on the actual Young's modulus is realized by calculating the percentage decrease of the Young's modulus compared to the initial value, for example, a decrease of 5% to 10% is slight erosion, a decrease of 10% to 20% is moderate erosion, and a decrease exceeding 20% is severe erosion. For the calculation of the percentage decrease, the formula (initial value - actual value) / initial value x 100% can be used, and for the judgment standard, a threshold trigger can be set to output a warning signal.

[0061] The embodiment of the application quantifies the erosion judgment standard by the degree of decrease of the Young's modulus, which quantifies the abstract erosion state, such as the levels of slight, moderate, and severe, providing clear and operable decision-making basis. This quantification method is convenient for integration into an automatic system to realize real-time early warning and maintenance scheduling, thereby improving the refinement and intelligence level of ladle management.

[0062] In one embodiment, the collection of the real vibration acceleration signal is realized by a vibration sensor installed on the outside of the ladle wall.

[0063] In application, the collection of the real vibration acceleration signal is realized by a vibration sensor, which is installed on the outside of the ladle wall to avoid the influence of high-temperature corrosion environment. For sensor deployment, magnetic attraction or bolt fixation can be used to ensure stable contact, and for signal transmission, shielded cable can be used to connect the data acquisition system to reduce interference.

[0064] The collecting mode of the embodiment of the application avoids damage of high temperature and corrosion inside the ladle to the sensor, prolongs the service life of the equipment, simplifies the deployment and maintenance process through outside installation, reduces the implementation cost, and ensures the continuity of signal collection, so that the method has high feasibility and popularization value in an industrial field.

[0065] In one embodiment, a model verification step is further included: Specifically, a 1:3 scale water model of the ladle (water replaces molten steel, and air replaces argon) is built, the bubble flow pattern and ladle wall vibration data in the water model are collected, and the calculation results of the multiphase flow model and the fluid-structure coupling model are compared to verify the accuracy of the model.

[0066] In one embodiment, the implementation process of the application is further described in combination with specific experimental data: Among them, the experimental device and parameter settings are as follows: Ladle prototype: effective volume corresponding to molten steel depth 3.15m, slag thickness 0.1m; Numerical simulation tool: ANSYS Workbench (including Fluent, Transient structural, Systemcoupling modules); Argon blowing parameters: argon flow rate 0.006kg / s, bubble diameter 0.02m, argon blowing time 12s; Vibration signal collection: sampling frequency 81.25Hz, collection period 0~2s (bubble flow rising stage); Young's modulus variable: 5 groups of experiments are set, E is 300GPa, 297GPa, 294GPa, 291GPa respectively.

[0067] Among them, the multiphase flow model verification is as follows: The molten steel flow field streamline is calculated by Fluent: when argon blowing starts, the bubble flow drives the molten steel to form a local circulation, the streamline is in the form of "small vortex" above the gas permeable roller, and the molten steel mainly flows in the bottom area; with the rising of the bubble flow, the streamline gradually extends upward, the range expands, the molten steel is sucked from the bottom to the upper part, and the top molten steel also starts to participate in the circulation, and the mixing is more complete; finally, the streamline tends to be regular and symmetrical, forming a "columnar" circulation through the lower part of the ladle, the flow path is stable, and the flow field gradually reaches dynamic balance (as shown in Figure 2 , which is consistent with the bubble flow pattern of the 1:3 water model experiment (as shown in FIG. 6), verifying the accuracy of the multiphase flow model.

[0068] Among them, the vibration signal analysis is as follows: Wavelet analysis is performed on the vibration acceleration signals of the 5 groups of experiments: Wavelet transform results (asFigure 4 0~0.125s, a high amplitude region (0.7~0.8Hz) appears (initial bubble impact), 0.125~0.25s, amplitude decreases, 0.25s later, the signal tends to be stable; Vibration amplitude extraction: the amplitude A corresponding to scale 2 is 0.238m / s 2 (E=300GPa), 0.240m / s 2 (E=297GPa), 0.244m / s 2 (E=294GPa), 0.246m / s 2 (E=291GPa), the amplitude increases linearly with the decrease of E; Linear model fitting: E=0.5178±0.02786 A, residual sum of squares , correlation coefficient-0.98995, the accuracy meets the requirements (as shown in FIG. 8).

[0069] Wherein, the actual erosion judgment example is as follows: A steel plant 130t ladle field monitoring: Collect vibration signals, wavelet analysis shows that the amplitude A corresponding to scale 2 is 0.243m / s 2 ; Substituting the linear model: E=0.5178-9.33333×10 -4 -0.243≈290.5GPa; Erosion degree judgment: initial E=300GPa, decrease amplitude≈3.2%, determined as slight erosion, it is suggested to maintain the current argon blowing parameters, and monitor again after 10 furnace times.

[0070] It should be understood that the size of the serial number of each step in the above embodiment does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the application.

[0071] The embodiments of the application also provide a ladle argon blowing process package wall erosion monitoring device for executing the steps in the above-mentioned ladle argon blowing process package wall erosion monitoring method embodiments. The ladle argon blowing process package wall erosion monitoring device can be a virtual device (virtual appliance) in an electronic device, which is run by a processor of the electronic device, or can be the electronic device itself.

[0072] As Figure 9 shown, the ladle argon blowing process package wall erosion monitoring device 100 provided by the embodiments of the application comprises: A collection module 101 for collecting the real vibration acceleration signal of the package wall in the ladle argon blowing process; The feature extraction module 102 is configured to extract a specific vibration amplitude of the real vibration acceleration signal. The Young's modulus determination module 103 is configured to substitute the specific vibration amplitude into a pre-established linear correlation model between the specific vibration amplitude and the Young's modulus, and inversely deduce an actual Young's modulus. The erosion determination module 104 is configured to determine a wall erosion degree based on the actual Young's modulus.

[0073] In applications, each module in the ladle argon blowing process wall erosion monitoring device can be a software program module, can be realized by different logic circuits integrated in a processor, or can be realized by multiple distributed processors.

[0074] As shown in Figure 10 The embodiments of the present application also provide an electronic device 200, which comprises at least one processor 201 (only one processor is shown in the figure), a memory 202, and a computer program 203 stored in the memory 202 and executable on the at least one processor 201, wherein the processor 201 implements the steps in each of the above method embodiments when executing the computer program 203. Figure 10

[0075] In applications, the electronic device can include, but is not limited to, a processor and a memory. Those skilled in the art can understand that Figure 7 The electronic device is only an example and does not constitute a limitation on the electronic device, and can include more or fewer components than those shown, or combine certain components, or different components.

[0076] In applications, the processor can be a central processing unit (CPU), and the processor can also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0077] ​In applications, the storage can be an internal storage unit of the electronic device, such as a hard disk or a memory of the electronic device, in some embodiments. The storage can also be an external storage device of the electronic device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, and the like, in other embodiments. Further, the storage can include both the internal storage unit and the external storage device of the electronic device. The storage is used to store an operating system, an application program, a BootLoader, data, and other programs, such as program codes of computer programs, and the like. The storage can also be used to temporarily store data that has been output or is to be output.

[0078] It should be noted that the information interaction and execution process between the above apparatuses / units are based on the same concept as the method embodiments of the present application, and the specific functions and technical effects brought by the above apparatuses / units can be referred to the method embodiments part, which will not be repeated here.

[0079] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above-mentioned division of functional units and modules is taken as an example, and in actual application, the above-mentioned functions can be completed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to complete all or part of the above-described functions. Each functional unit and module in the embodiments can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of software functional unit. In addition, the specific names of each functional unit and module are only for easy distinction, and do not limit the protection scope of the present application. The specific working process of the units and modules in the system can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0080] The embodiments of the present application also provide a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the steps in each of the above method embodiments.

[0081] The embodiments of the present application provide a computer program product, which includes a computer program. When the computer program product is run on an electronic device, the electronic device is caused to execute the steps in each of the above method embodiments.

[0082] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. The computer program can implement the steps of each method embodiment when executed by a processor. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate forms. The computer readable medium at least includes any entity or device capable of carrying the computer program code to the device / equipment, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium. For example, U disk, mobile hard disk, magnetic disk or optical disk, etc. In some jurisdictions, according to legislation and patent practice, the computer readable medium can not be an electrical carrier signal and a telecommunication signal.

[0083] In the above embodiments, the description of each embodiment has its own focus, and the parts not described or recorded in detail in a certain embodiment can be referred to the related description of other embodiments.

[0084] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0085] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the above-described device embodiments are only schematic, and the division of the modules or units is only a logical function division, and there can be another division in actual implementation, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed mutual elements can be indirect coupling or communication connection through some interface, device or unit, and can be electrical, mechanical or other forms.

[0086] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may also be distributed to multiple network units. Part or all of the units can be selected to achieve the purpose of the embodiment scheme according to actual needs.

[0087] The above embodiments are only used to illustrate the technical solutions of the present application, but not limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can still be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method for monitoring the wall erosion of a ladle argon blowing process, characterized in that, The method comprises: collecting a real vibration acceleration signal of a ladle wall during ladle argon blowing; extracting a specific vibration amplitude of the real vibration acceleration signal; substituting the specific vibration amplitude into a pre-established linear correlation model of the specific vibration amplitude and Young's modulus to inversely deduce an actual Young's modulus; determining a ladle wall erosion degree based on the actual Young's modulus.

2. The ladle argon stirring process wall erosion monitoring method as claimed by Claim 1, wherein, The method further comprises: establishing a three-phase flow model of argon, molten steel and slag in the ladle to simulate bubble flow rising flow field characteristics; establishing a fluid-structure coupling model coupled with the three-phase flow model and taking the Young's modulus as a representation of the ladle wall erosion degree; simulating the bubble flow rising flow field characteristics by using the fluid-structure coupling model to obtain vibration acceleration data corresponding to different Young's moduli; extracting specific vibration amplitudes of the vibration acceleration data corresponding to different Young's moduli; fitting the linear correlation model of the specific vibration amplitude and Young's modulus based on the corresponding relationship between the specific vibration amplitude and the Young's modulus.

3. The ladle argon flushing process wall erosion monitoring method as claimed in claim 2, wherein, The three-phase flow model adopts Realizable The two-equation model describes the turbulent characteristics of the liquid steel, and the VOF method is used to capture the three-phase interface. The control equations of the three-phase flow model include continuity equation, momentum conservation equation, turbulent kinetic energy k equation and turbulent dissipation rate ε equation.

4. The ladle argon flushing process wall erosion monitoring method as claimed in claim 2, wherein After the real vibration acceleration signal of the ladle wall during ladle argon blowing is collected, the method further comprises: performing wavelet threshold denoising on the real vibration acceleration signal; performing continuous wavelet transform time-frequency analysis on the denoised signal, and extracting a specific vibration amplitude from the time-frequency analysis result.

5. The ladle argon flushing process wall erosion monitoring method as claimed in claim 4, wherein, The wavelet threshold denoising comprises: filtering noise by using a hard threshold function; wherein the threshold of the hard threshold function is determined by unbiased likelihood estimation.

6. The ladle argon flushing process wall erosion monitoring method as claimed in claim 4, wherein, The specific vibration amplitude is a vibration amplitude of a characteristic frequency generated when the bubble flow initially impacts the ladle wall.

7. The ladle argon flushing process wall erosion monitoring method as claimed in claim 1, wherein, The determination of the ladle wall erosion degree based on the actual Young's modulus comprises determining the ladle wall erosion degree based on the degree of decrease of the actual Young's modulus compared with the initial Young's modulus, and specifically comprising: when the degree of decrease of the actual Young's modulus compared with the initial Young's modulus is in the range of 5% to 10%, determining that the ladle wall is slightly eroded; when the degree of decrease of the actual Young's modulus compared with the initial Young's modulus is in the range of 10% to 20%, determining that the ladle wall is moderately eroded; when the degree of decrease of the actual Young's modulus compared with the initial Young's modulus exceeds 20%, determining that the ladle wall is severely eroded.

8. The ladle argon flushing process wall erosion monitoring method as claimed in claim 1, wherein, The collection of the real vibration acceleration signal is realized by a vibration sensor installed on the outside of the ladle wall.

9. A ladle argon flushing process wall erosion monitoring device, characterized by, The method comprises: a collecting module configured to collect a real vibration acceleration signal of a ladle wall during ladle argon blowing; a feature extraction module configured to extract a specific vibration amplitude of the real vibration acceleration signal; a Young's modulus determination module configured to substitute the specific vibration amplitude into a pre-established linear correlation model of the specific vibration amplitude and Young's modulus to inversely deduce an actual Young's modulus; an erosion determination module configured to determine a ladle wall erosion degree based on the actual Young's modulus.

10. An electronic device, comprising: The electronic device comprises a processor, a memory, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the electronic device implements the method according to any one of claims 1 to 8.

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