Converter tapping and roughing control system based on emissivity

Abstract

The invention relates to a converter tapping and roughing control system based on emissivity. The system comprises a spectrum detection system, a central processing system, an alarm display system and a tapping hole control system, the spectrum detection system is used for acquiring a plurality of wavelengths and corresponding gray values of a material in a set range in the tapping process of the converter; the central processing system is used for receiving the wavelengths and the corresponding gray values obtained by the spectrum detection system to obtain the spectral radiation brightness corresponding to the wavelengths; obtaining the spectral emissivity of the material in the converter by using a temperature-emissivity separation inversion method based on each wavelength and the corresponding spectral radiance; based on the spectral emissivity, an alarm signal is sent out during slag tapping; and the alarm display system and the tapping hole control system respectively carry out alarm operation and tapping hole closing control operation when receiving the alarm signal sent by the central processing system. The slag discharging condition can be accurately judged, and better steel can be obtained easily.

Description

Technical Field

[0001] The present invention relates to the technical fields of testing and steelmaking, and particularly relates to a converter tapping slag control system based on emissivity. Background Art

[0002] During the converter tapping process, when most of the molten steel is discharged, a strong eddy current will be generated at the tapping hole of the converter. This eddy current will carry out the slag floating on the surface of the molten steel. The outflow of the slag will affect the purity of the molten steel during tapping, bring difficulties to the subsequent refining of the molten steel, or cause a decline in the performance of the cast steel parts. Therefore, during converter tapping, it is necessary to block the slag in the converter to control the amount of slag in the tapped molten steel.

[0003] The existing control of the amount of slag in converter tapping mainly relies on manual operation by operators. That is, in the later stage of converter tapping, the operator adds a slag blocking ball or a slag blocking plug at the tapping hole according to the slag discharge situation in the molten steel to control the amount of slag in the tapped molten steel. Judging the amount of slag in the molten steel by the human eye has a large time lag, strong subjectivity, and great uncertainty. Therefore, it is necessary to develop a new converter tapping slag control system to reduce the amount of slag in tapping. Summary of the Invention

[0004] In view of the above analysis, an embodiment of the present invention aims to provide a converter tapping slag control system based on emissivity to solve the problem of low accuracy in judging the slag situation during the existing converter tapping process.

[0005] The object of the present invention is mainly achieved through the following technical solutions:

[0006] The present invention provides a converter tapping slag control system based on emissivity, including a spectral detection system, a central processing system, an alarm display system, and a tapping hole control system;

[0007] The spectral detection system is used to obtain multiple wavelengths and corresponding gray values of materials within a set range during the converter tapping process;

[0008] The central processing system is used to receive the wavelengths and corresponding gray values obtained by the spectral detection system to obtain the spectral radiance corresponding to each wavelength; use the temperature-emissivity separation inversion method based on each wavelength and the corresponding spectral radiance to obtain the spectral emissivity of the materials in the converter; and send an alarm signal when slagging based on the spectral emissivity;

[0009] When receiving the alarm signal sent by the central processing system, the alarm display system and the tapping hole control system respectively perform alarm operations and control operations to close the tapping hole.

[0010] Further, the central processing system includes a data receiving and processing module, a temperature emissivity separation and inversion module, and an emissivity analysis module;

[0011] The data receiving and processing module receives the wavelengths and corresponding gray values acquired by the spectral detection system, and obtains the spectral radiance corresponding to each wavelength by using the pre-calibrated gray value - spectral radiance data;

[0012] The temperature emissivity inversion module receives the wavelengths and corresponding spectral radiance, and uses the temperature-emissivity separation and inversion method to obtain the spectral emissivity of the material in the converter;

[0013] The emissivity analysis module determines the state of the material based on the spectral emissivity obtained by the temperature emissivity separation and inversion module, and issues an alarm signal when the spectral emissivity exceeds the set threshold.

[0014] Further, the alarm display system includes an LCD screen, a warning light, and a buzzer; when receiving the alarm signal sent by the central processing system, the slag discharge information is displayed on the LCD screen, and the alarm light and the buzzer are activated to remind the operator to throw a slag blocking ball into the converter;

[0015] When the tapping hole control system receives the alarm signal sent by the central processing system, the tapping hole control system performs an operation to automatically close the tapping hole or the operator manually closes the tapping hole according to the pre-setting.

[0016] Further, the receiving the wavelengths and corresponding spectral radiance and using the temperature-emissivity separation and inversion method to obtain the spectral emissivity of the material in the converter includes:

[0017] Based on the spectral radiance of each wavelength, the blackbody temperature of the ideal blackbody corresponding to each wavelength is obtained by using the Planck blackbody radiation formula

[0018] Based on the spectral radiance corresponding to each wavelength and the blackbody temperature corresponding to each wavelength, the temperature of the inverted material and the spectral emissivity corresponding to each wavelength are obtained by using the EM optimization strategy.

[0019] Further, in one iteration process of the EM optimization strategy:

[0020] Obtain the initial temperature of this iteration and the initial spectral emissivity corresponding to each wavelength;

[0021] In the maximization step of the EM optimization strategy: Based on the initial spectral emissivity of each wavelength, the free energy minimization method is used as the maximum likelihood function of the EM optimization strategy to calculate the optimal temperature as the hidden parameter of the EM optimization strategy;

[0022] In the expectation step of the EM optimization strategy: Based on the optimal temperature, obtain the spectral emissivity of each wavelength at this temperature, and use the spectral emissivity fitting smoothing method to obtain the smoothed spectral emissivity of each wavelength as the spectral emissivity expectation value corresponding to each wavelength;

[0023] The optimal temperature is used as the initial temperature for the next iteration, and the spectral emissivity expectation value corresponding to each wavelength is used as the initial spectral emissivity for the next iteration;

[0024] When the spectral emissivity expectation value corresponding to each wavelength and the initial spectral emissivity of each wavelength satisfy the convergence condition, the obtained optimal temperature and the spectral emissivity of each wavelength are used as the inverted temperature and the spectral emissivity corresponding to each wavelength, and the iteration ends.

[0025] Furthermore, the optimal temperature is calculated using the free energy minimization method based on the initial emissivity of each wavelength. The formula of the free energy minimization method is:

[0026]

[0027]

[0028] where T opt is the optimal temperature; ΔA is the change in internal energy; C V is the heat capacity of the material; is the initial spectral emissivity at wavelength λ i ; is the spectral emissivity of the material at wavelength λ i at temperature T opt ;

[0029] Based on the optimal temperature, the spectral emissivity of each wavelength at this temperature is obtained using the following formula

[0030]

[0031] Furthermore, the use of the spectral emissivity fitting smoothing method to fit and smooth the spectral emissivity of each wavelength includes:

[0032] Based on the spectral emissivity corresponding to each wavelength, obtain the single-wavelength radiation entropy of each wavelength:

[0033] Use the high-order polynomial fitting method for the single-wavelength radiation entropy of each wavelength to obtain the smoothed wavelength radiation entropy;

[0034] Based on the smoothed wavelength radiation entropy, obtain the fitted and smoothed spectral emissivity.

[0035] Further, the high-order polynomial fitting method includes: for each wavelength, using a kernel function as a weight to perform local polynomial kernel regression to obtain a high-order polynomial as a regression function, and using the regression function to calculate the single-wavelength radiation entropy of each wavelength as the smoothed wavelength radiation entropy; wherein, the local polynomial kernel regression includes: selecting a preset number of wavelengths adjacent to this wavelength, and performing polynomial fitting based on the kernel function within this range.

[0036] Further, the coefficients of the high-order polynomial are calculated using the following formula:

[0037] θ=(X T K T KX) -1 X T K T KY

[0038] wherein, θ is the coefficient vector of the polynomial function; X is the Vandermonde matrix with respect to the wavelength; K is the diagonalized kernel function matrix; and Y is the single-wavelength radiation entropy vector of each wavelength.

[0039] Further, the initial temperature of the first iteration is the maximum temperature T among the blackbody temperatures of each wavelength max ;

[0040] The initial spectral emissivity of each wavelength in the first iteration is obtained using the Planck blackbody radiation formula based on the maximum temperature.

[0041] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0042] 1. The present invention uses the change in material emissivity to judge the time when steel slag appears, which is not affected by environmental and human subjective factors, has high judgment accuracy, makes the tapping accuracy of the converter higher, and is easy to obtain better steel.

[0043] 2. The emissivity-temperature separation inversion algorithm used in the present invention can separately calculate the spectral emissivity and temperature of the material only by relying on the heat capacity function of the material, and this function is known for most materials, with simple calculation and high reliability.

[0044] 3. The present invention uses a hyperspectral emissivity fitting and smoothing method, a physical modeling method for the spectral emissivity characteristics of materials based on probability, clarifies the relationship between entropy and the spectral emissivity of materials, makes the smoothed emissivity have a very clear physical meaning, satisfies various physical constraint conditions of the emissivity, and uses a high-order polynomial to fit the spectral radiation entropy, meeting the requirements of smoothing and continuity, and having a fast operation speed.

[0045] In the present invention, the above technical solutions can also be combined with each other to achieve more preferred combination solutions. Other features and advantages of the present invention will be described in the subsequent specification, and some advantages can be made obvious from the specification, or understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained from the content specifically pointed out in the specification and the drawings. Description of the Drawings

[0046] The drawings are only for the purpose of showing specific embodiments, and are not considered as limiting the present invention. Throughout the drawings, the same reference signs denote the same components.

[0047] Figure 1 It is a schematic structural diagram of a ladle tapping slag control system based on emissivity in an embodiment of the present invention;

[0048] Figure 2 It is a schematic diagram of the spectral emissivity of molten steel and slag at 1600 °C in an embodiment of the present invention;

[0049] Figure 3 It is a schematic diagram of the EM optimization strategy process in an embodiment of the present invention;

[0050] Figure 4 It is a schematic diagram of the process of the spectral emissivity fitting smoothing method in an embodiment of the present invention. Detailed Embodiments

[0051] The following will specifically describe the preferred embodiments of the present invention with reference to the drawings. The drawings form a part of this application and are used together with the embodiments of the present invention to explain the principles of the present invention, and are not used to limit the scope of the present invention.

[0052] A specific embodiment of the present invention discloses a ladle tapping slag control system based on emissivity, as Figure 1 shown, including: a spectral detection system, a central processing system, an alarm display system, and a tapping hole control system;

[0053] The spectral detection system is used to obtain the wavelengths and corresponding gray values of materials in a set range during the ladle tapping process of the converter;

[0054] Specifically, the spectral detection system is a spectrometer set at the ladle tapping operation site of the converter, which can obtain the wavelengths and their corresponding gray values of the molten steel flowing out of the tapping hole within the set wavelength range of the spectrometer;

[0055] In this embodiment, as Figure 2 shown, the change of emissivity of molten steel and slag at a high temperature of 1600 degrees, and the selected wavelength range of the measurement spectrometer is 7-14 μm.

[0056] The central processing system includes: a data receiving and processing module, a temperature emissivity separation and inversion module, and an emissivity analysis module;

[0057] The data receiving and processing module receives the wavelengths and corresponding gray values acquired by the spectral detection system, and uses the pre-calibrated gray value - spectral radiance data to obtain the spectral radiance corresponding to each of the wavelengths;

[0058] The temperature emissivity separation and inversion module receives the wavelengths and corresponding spectral radiance, and uses the temperature-emissivity separation and inversion method to obtain the spectral emissivity of the material in the converter;

[0059] The emissivity analysis module determines the state of the material based on the spectral emissivity obtained by the temperature emissivity separation and inversion module, and issues an alarm signal when the spectral emissivity exceeds a set threshold;

[0060] Specifically, the data receiving module receives the wavelengths and corresponding gray values acquired by the spectral detection system, filters out the error data, and uses the pre-calibrated gray-spectral radiance data to obtain the spectral radiance corresponding to each of the wavelengths;

[0061] It should be noted that the filtering of error data is due to the fact that the signal-to-noise ratio at both ends of the wavelength region acquired by the spectrometer used to acquire data is relatively low, and negative values will appear after the gray value subtracts the background. Therefore, it is necessary to remove it.

[0062] Furthermore, in the temperature emissivity separation and inversion module, based on the wavelengths and spectral brightness of the material in a specific range of the data receiving and analysis module, the following method is used to invert the temperature and emissivity of the molten steel in the converter, including:

[0063] Based on the spectral radiance corresponding to each wavelength of the material in a specific range, according to Planck's quantum hypothesis, the blackbody temperature corresponding to each wavelength of the ideal blackbody is obtained using the following formula:

[0064]

[0065] where, is the wavelength λ i at temperature the spectral radiance of the ideal blackbody; C1 is the first radiation constant, with a value of 3.74×10 -16 (W×m 2 ); C2 is the second radiation constant, with a value of 1.4398×10 -2 (m×K).

[0066] Further, based on the spectral radiance corresponding to each wavelength and the blackbody temperature corresponding to each wavelength, the EM optimization strategy is used to obtain the temperature of the material after inversion and the spectral emissivity corresponding to each wavelength.

[0067] Specifically, the EM optimization strategy is an iterative optimization strategy. Each iteration in its calculation method consists of two steps. One is the expectation step, i.e., the E step, and the other is the maximization step, i.e., the M step, which is to solve the parameter estimation problem in the case of missing data (including latent variables).

[0068] Further, the basic idea of the EM optimization strategy is as follows: First, based on the given observed data, estimate the values of the model parameters (initialization); then, based on the parameter values estimated in the previous step, estimate the values of the missing data, and then re-estimate the parameter values according to the estimated missing data plus the previously observed data, and then iterate repeatedly until convergence, and the iteration ends.

[0069] In this embodiment, as Figure 3 shown, the EM optimization strategy includes the following steps in one iteration process:

[0070] In one iteration process:

[0071] Step S301: Obtain the initial temperature of this iteration and the initial spectral emissivity corresponding to each wavelength;

[0072] Specifically, in the first iteration process, the initial temperature is the maximum temperature T among the blackbody temperatures of each wavelength max .

[0073] In the first iteration process, the initial spectral emissivity of each wavelength is obtained based on the maximum temperature using the following formula:

[0074]

[0075]

[0076] where, is the initial spectral emissivity of wavelength λ i ; T max is the maximum temperature; I obs (λ i ) is the spectral radiance corresponding to the wavelength λ to be separated i ; I B (λ i , T max ) is the spectral radiance of the ideal blackbody at wavelength λ i at temperature T max ; e is the natural constant.

[0077] Step S302. In the maximization step of the EM optimization strategy: Using the free energy minimization method as the maximum likelihood function of the EM optimization strategy, calculate the optimal temperature as the hidden parameter of the EM optimization strategy based on the initial spectral emissivity of each wavelength.

[0078] Specifically, when calculating the emissivity at a certain wavelength point according to the measured data, it often implies that the data is under certain temperature conditions, and it also implies that the emissivities of other wavelength points can be calculated based on this temperature, that is, the obtained emissivity information is related to the temperature.

[0079] In this embodiment, the emissivity-temperature separation algorithm based on free energy minimization refers to calculating the entropy using the spectral emissivity and calculating the internal energy using the material heat capacity, and obtaining the optimal temperature through free energy minimization.

[0080] In statistics, the KL divergence is generally used to measure the "distance" between two probability distribution functions, and can describe the relative distance between two distributions P i and Q i to a certain extent:

[0081]

[0082] Similarly, in thermodynamics, the KL divergence corresponds to the sum of the entropy changes of the system and the environment in these two different states:

[0083]

[0084] where, ΔS is the change in entropy; ΔU env is the change in the internal energy of the environment; ΔS sys is the entropy of the system; ΔS env is the entropy of the environment; T0 is the temperature.

[0085] Specifically, according to the definition of Helmholtz free energy:

[0086] A = U - TS

[0087] Assume that the volume and energy of the system can be ignored relative to the environment, and the temperature change of the environment before and after the energy exchange with the system can be ignored. Then the total free energy change of the system and the environment before and after the state change can be defined as:

[0088] ΔA = ΔU - TΔS = ΔU - TD KL (ε2||ε1)

[0089] where, ΔU is the change in the internal energy of the system, which can be calculated through the heat capacity, and the formula is:

[0090] ΔU = C v (T - T0)

[0091] Among them, C v is the heat capacity of the material, which is generally a function of temperature: C v (T) = f(T); Many scientists have accurately measured the heat capacity values of various substances at various temperatures by experimental methods and obtained empirical expressions representing the relationship between heat capacity and temperature.

[0092] Furthermore, the optimal temperature T is calculated by using the free energy minimization method as the maximum likelihood function in the maximization step of the EM optimization strategy opt ;

[0093] Specifically, the formula of the free energy minimization method is:

[0094]

[0095]

[0096]

[0097] Among them, T opt is the optimal temperature, which is a hidden parameter of the EM optimization strategy; ΔA is the change in internal energy; C V is the heat capacity of the material; is the initial spectral emissivity at wavelength λ i ; I obs (λ i ) is the spectral radiance corresponding to the wavelength λ i to be separated; I B (λ i , T opt ) is the spectral radiance of an ideal blackbody at wavelength λ i at temperature T opt .

[0098] Step S303, in the expectation step of the EM optimization strategy: Based on the optimal temperature, obtain the spectral emissivity of each wavelength at this temperature and use the spectral emissivity fitting smoothing method to obtain the smoothed spectral emissivity of each wavelength as the spectral emissivity expectation value corresponding to each wavelength;

[0099] Specifically, use the following formula to calculate the spectral emissivity of each wavelength at the optimal temperature

[0100]

[0101] Furthermore, use the spectral emissivity fitting smoothing method to fit and smooth the spectral emissivity of each wavelength;

[0102] Specifically, during the measurement process, due to reasons such as detector noise, wavelength calibration, and stray radiation interference, the measured data is always accompanied by a large amount of fluctuations. Therefore, the calculated spectral emissivity of the material is also accompanied by a large amount of fluctuations. Effective fitting and smoothing of the spectral emissivity of the material is also crucial in this embodiment.

[0103] Further, as Figure 4 shown, the spectral emissivity fitting and smoothing method includes:

[0104] Step S3031: Obtain the single-wavelength radiation entropy of each wavelength based on the spectral emissivity corresponding to each wavelength;

[0105] Specifically, according to the probability characteristics of the emissivity and the Lebesgue measure, the entropy of the system at this wavelength can be measured by the following formula:

[0106]

[0107] where g(m) is the degeneracy of the state when exactly m particles radiate and de-excite, and its numerical value is indicating that there are g(m) microscopic states with the same energy.

[0108] Further, from the above formula, it can be deduced that:

[0109] H λ =-N[ε λ lnε λ +(1 - ε λ )ln(1 - ε λ )]

[0110] Therefore, the single-wavelength radiation entropy of a single particle at each wavelength is:

[0111]

[0112] where is the single-wavelength radiation entropy at wavelength λ i ; is the spectral emissivity corresponding to wavelength λ i ; in order to avoid the situation where the spectral emissivity is greater than or equal to 1 or less than or equal to 0 (in these cases the calculation result is a complex number), the modulus of the calculation result is taken to obtain

[0113] It can be seen from this that the entropy of the system is equal to the entropy of a single particle multiplied by the total number of particles N, and its magnitude is related to the emissivity of the material in different wavelength bands.

[0114] Step S3032: Use the high-order polynomial fitting method for the single-wavelength radiation entropy of each wavelength to obtain the smoothed wavelength radiation entropy;

[0115] Specifically, the high-order polynomial fitting method includes: for each wavelength, use the kernel function as the weight to perform local polynomial kernel regression to obtain a high-order polynomial as the regression function, and use the regression function to calculate the single-wavelength radiation entropy of each wavelength as the smoothed wavelength radiation entropy; where, the local polynomial kernel regression includes: select a preset number of wavelengths adjacent to this wavelength, and perform polynomial fitting based on the kernel function within this range.

[0116] It should be noted that the preset number is the number of data points participating in the calculation on both sides of the smoothing point, which controls how many adjacent data points are used in the calculation; the larger the preset number range, the smoother the result. Preferably, the preset number N is selected to be 10 - 50.

[0117] Furthermore, according to solid-state physics theory, the spectral emissivity reflects the microscopic photoacoustic coupling characteristics of the material, and it should exhibit certain short-range continuity, smoothness, and certain long-range correlation in hyperspectral data. The smoothness of the material spectral emissivity means that the derivative of the spectral emissivity is continuous when the wavelength changes. The short-range correlation and long-range correlation are the external manifestations of the material energy band structure. When the material is a mixture, the long-range correlation and short-range correlation weaken, but still maintain relatively high spectral continuity and smoothness.

[0118] Furthermore, the continuity and smoothness of the material spectral emissivity are due to the fact that the radiation entropy H at different wavelengths at the microscopic level λ has smooth and continuous characteristics.

[0119] Specifically, high-order polynomial fitting is a commonly used method in data analysis and machine learning. It can fit a set of data into a high-order polynomial model. This method can improve the fitting accuracy of the data to a certain extent.

[0120] The basic idea of high-order polynomial fitting is to find an optimal polynomial function to fit the given data set, so as to minimize the error between the fitting function and the original data set. To achieve this goal, we need to select a suitable polynomial function and solve the coefficients of the polynomial function by the least squares method.

[0121] Specifically, we can select an nth-degree polynomial function about the independent variable λ i to fit the data. In this embodiment, this polynomial function can be expressed as the regression function:

[0122] H(λ i ) = a0 + a1λ i + a2λi 2 +a3λ i 3 +…+a n λ i n

[0123] where λ i is the wavelength value of the i-th wavelength; a0, a1…a n are the coefficients of the polynomial function, and n is the order of the polynomial function. By the least squares method, we can solve for the optimal values of these coefficients, thus obtaining an optimal polynomial function to fit the data.

[0124] It should be noted that high-order polynomial fitting may cause overfitting problems in some cases. Overfitting means that when fitting the data, in order to achieve a better fitting effect, the original data set is overfitted, resulting in a poor prediction effect for new data. Therefore, when performing high-order polynomial fitting, it is necessary to select the order of the polynomial according to the specific situation and make appropriate adjustments and optimizations.

[0125] Specifically, the order of the polynomial is from 2 to 11, preferably an odd order.

[0126] In this embodiment, the order is preferably 5.

[0127] As can be seen from the above, as long as the polynomial coefficients of the radiation entropy at different wavelengths are obtained, the emissivity of the material can be fitted and smoothed. However, if a fixed polynomial is used, this fitting method has a strong long-range correlation, which does not conform to the actual material characteristics.

[0128] Therefore, in this embodiment, kernel regression is used to fit the entropy, so that while meeting the requirements of smoothness and continuity, the hard constraint of its long-range correlation is reduced.

[0129] Specifically, traditional linear regression can only fit a straight line. Kernel regression is a regression method based on nonlinear mapping, which is a method that only uses multiple data points near the data point for regression. In essence, it uses the kernel function as the weight function to establish a nonlinear regression model.

[0130] Furthermore, according to the least squares method, local polynomial kernel regression is to solve the coefficients θ of the polynomial function to minimize the following objective function J(θ):

[0131] J(θ) = (Xθ - Y) T K(Xθ - Y)

[0132] where θ is the coefficient vector of the polynomial function; X is the Vandermonde matrix with respect to the wavelength; K is the diagonalized kernel function matrix; and Y is the single-wavelength radiation entropy vector of each of the wavelengths.

[0133] Therefore, according to the coefficient calculation formula of the polynomial function can be obtained:

[0134]

[0135] Furthermore, the Vandermonde matrix X for the wavelength is:

[0136]

[0137] where λ is the smoothed wavelength; i is the serial number of the i-th wavelength currently selected; N is the preset quantity.

[0138] It should be noted that in the matrix, if i - N is less than 1, the calculation starts from 1; if i + N is greater than the total number of wavelengths within the wavelength range to be fitted, the calculation is only performed up to the last wavelength.

[0139] Furthermore, the diagonalized kernel function matrix K is:

[0140] K = diag(k(λ,λ i-N ),…k(λ,λ i ),…k(λ,λ i+N ))

[0141] where k(λ,λ i ) is the kernel function; λ is the smoothed wavelength; i is the serial number of the i-th wavelength currently selected; N is the preset quantity.

[0142] Specifically, the kernel function defines the similarity measurement method of the input data in the feature space. Commonly used kernel functions include Gaussian kernel function, polynomial kernel function, sigmoid kernel function, etc.

[0143] Preferably, the Gaussian kernel function regression model is selected in the present invention:

[0144]

[0145] where σ is the standard deviation.

[0146] Specifically, the Gaussian kernel function can be regarded as a weight negatively correlated with the distance from the center; during smoothing, adjusting the standard deviation is to adjust the influence degree of the surrounding wavelengths on the current wavelength. Increasing σ increases the influence degree of the distant wavelengths on the central wavelength, and the filtering result is smoother.

[0147] Furthermore, the single-wavelength radiation entropy vector of the wavelength is:

[0148]

[0149] where is the single-wavelength radiation entropy with wavelength λ i ; i is the sequence number of the i-th wavelength currently selected; N is the preset quantity.

[0150] So far, after substituting the wavelength λ i into the regression function H(λ), the calculated H(λ i ) is the entropy after smoothing for this wavelength

[0151] Step S3033: Obtain the fitted and smoothed spectral emissivity based on the smoothed wavelength radiation entropy.

[0152] Specifically, based on the smoothed wavelength radiation entropy, the following formula is used to obtain the fitted and smoothed spectral emissivity of the wavelength range to be fitted:

[0153]

[0154] where is the spectral emissivity of the smoothed wavelength λ i , which is the expected value of the spectral emissivity of the wavelength λ i for this iteration; is the single-wavelength radiation entropy of the smoothed wavelength λ i .

[0155] Step S304: Use the optimal temperature as the initial temperature for the next iteration, and the expected values of the spectral emissivities corresponding to each wavelength as the initial spectral emissivities for the next iteration, and perform the next iteration;

[0156] Step S305: When the expected values of the spectral emissivities corresponding to each wavelength and the initial spectral emissivities corresponding to each wavelength satisfy the convergence condition, the obtained optimal temperature and the spectral emissivities of each wavelength are used as the temperature after inversion and the spectral emissivities corresponding to each wavelength, and the iteration ends.

[0157] Specifically, the method for judging the convergence condition is to calculate value, and when it is less than a specific value, it is judged to satisfy the convergence condition.

[0158] It should be noted that the specific value can be adjusted according to the actual situation and accuracy requirements; in this embodiment, the specific value is taken as 1E-8.

[0159] Furthermore, in this embodiment, the Anderson acceleration algorithm is preferably used to accelerate the iteration process of the EM optimization strategy, which can greatly improve the convergence speed of the algorithm.

[0160] Further, the alarm display system includes a liquid crystal display screen, a warning light, and a buzzer; when receiving the alarm signal sent by the central processing system, slag discharge information is displayed on the liquid crystal display screen, and the alarm light and the buzzer are activated to remind the operator to throw a slag blocking ball into the converter.

[0161] When the tapping hole control system receives the alarm signal sent by the central processing system, the tapping hole control system performs an operation to automatically close the tapping hole or the operator manually closes the tapping hole according to pre - settings.

[0162] It should be noted that the slag discharge information displayed on the liquid crystal display screen is to display the spectral emissivity with a red icon.

[0163] In summary, a converter steel - tapping slag - dropping control system based on emissivity according to an embodiment of the present invention has the following beneficial effects:

[0164] 1. The present invention uses the change of material emissivity to judge the time when steel slag appears, which is not affected by environmental and human subjective factors, and has high judgment accuracy, making the slag - dropping accuracy of the converter higher and it is easier to obtain better steel.

[0165] 2. The emissivity - temperature separation inversion algorithm used in the present invention can separately calculate and obtain the spectral emissivity and temperature of the material only by relying on the heat capacity function of the material, and this function is known for the vast majority of materials, with simple calculation and high reliability.

[0166] 3. The present invention uses a hyperspectral emissivity fitting and smoothing method and a physical modeling method for the spectral emissivity characteristics of materials based on probability, clarifies the relationship between entropy and the spectral emissivity of materials, makes the smoothed emissivity have a very clear physical meaning, and satisfies various physical constraint conditions of emissivity. At the same time, a high - order polynomial is used to fit the spectral radiation entropy, which meets the requirements of smoothing and continuity, and has a fast operation speed.

[0167] The above - mentioned content is only the preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A ladle slagging control system based on emissivity, characterized in that, It includes a spectral detection system, a central processing system, an alarm display system, and a tapping hole control system; The spectral detection system is used to obtain multiple wavelengths and corresponding gray values of materials within a set range during the tapping process of the converter; The central processing system is used to receive the wavelengths and corresponding gray values obtained by the spectral detection system to obtain the spectral radiance corresponding to each wavelength; use the temperature-emissivity separation inversion method based on each wavelength and the corresponding spectral radiance to obtain the spectral emissivity of the materials in the converter; and send an alarm signal during slagging; When receiving the alarm signal sent by the central processing system, the alarm display system and the tapping hole control system respectively perform alarm operations and control the operation of closing the tapping hole.

2. The system according to claim 1, wherein The central processing system includes a data reception and processing module, a temperature-emissivity separation inversion module, and an emissivity analysis module; The data reception and processing module receives the wavelengths and corresponding gray values obtained by the spectral detection system, and uses the pre-calibrated gray value-spectral radiance data to obtain the spectral radiance corresponding to each wavelength; The temperature-emissivity inversion module receives the wavelengths and corresponding spectral radiance and uses the temperature-emissivity separation inversion method to obtain the spectral emissivity of the materials in the converter; The emissivity analysis module determines the state of the materials based on the spectral emissivity obtained by the temperature-emissivity separation inversion module, and sends an alarm signal when the spectral emissivity exceeds the set threshold.

3. The system according to claim 2, wherein The alarm display system includes an LCD screen, a warning light, and a buzzer; when receiving the alarm signal sent by the central processing system, it displays slagging information on the LCD screen and activates the alarm light and the buzzer to remind the operator to throw a slag blocking ball into the converter; When receiving the alarm signal sent by the central processing system, the tapping hole control system automatically closes the tapping hole according to the pre-setting or the operator manually closes the tapping hole.

4. The system according to claim 2, wherein The receiving of the wavelengths and corresponding spectral radiance and using the temperature-emissivity separation inversion method to obtain the spectral emissivity of the materials in the converter includes: Based on the spectral radiance at each wavelength, the blackbody temperature of the ideal blackbody at each of the said wavelengths is obtained using the Planck blackbody radiation formula Based on the spectral radiance corresponding to each wavelength and the blackbody temperature corresponding to each wavelength, use the EM optimization strategy to obtain the temperature of the inverted material and the spectral emissivity corresponding to each wavelength.

5. The system according to claim 4, wherein The EM optimization strategy, in one iteration process: Obtain the initial temperature of this iteration and the initial spectral emissivity corresponding to each wavelength; In the maximization step of the EM optimization strategy: use the free energy minimization method as the maximum likelihood function of the EM optimization strategy based on the initial spectral emissivity of each wavelength to calculate the optimal temperature as the hidden parameter of the EM optimization strategy; In the expectation step of the EM optimization strategy: obtain the spectral emissivity of each wavelength at this temperature based on the optimal temperature and use the spectral emissivity fitting and smoothing method to obtain the smoothed spectral emissivity of each wavelength as the spectral emissivity expectation value corresponding to each wavelength; The optimal temperature is used as the initial temperature for the next iteration, and the expected values of the spectral emissivities corresponding to each of the wavelengths are used as the initial spectral emissivities for the next iteration; When the expected values of the spectral emissivities corresponding to each of the wavelengths and the initial spectral emissivities of each of the wavelengths satisfy the convergence condition, the obtained optimal temperature and the spectral emissivities of each of the wavelengths are used as the temperature and the spectral emissivities corresponding to each of the wavelengths after inversion, and the iteration ends.

6. The system according to claim 5, wherein The optimal temperature is calculated by using the free energy minimization method based on the initial emissivities of each of the wavelengths, wherein the formula of the free energy minimization method is: Among them, T opt is the optimal temperature; ΔA is the change in internal energy; C V is the heat capacity of the material; is the initial spectral emissivity at wavelength λ i ; is the spectral emissivity of the material at wavelength λ i at temperature T opt ; Based on the optimal temperature, the spectral emissivity of each of the wavelengths at this temperature is obtained using the following formula 7. The system according to claim 6, characterized in that, The fitting and smoothing of the spectral emissivities of each of the wavelengths by using the spectral emissivity fitting and smoothing method includes: Obtaining the single-wavelength radiation entropy of each of the wavelengths based on the spectral emissivities corresponding to each of the wavelengths; Obtaining the smoothed wavelength radiation entropy by using the high-order polynomial fitting method for the single-wavelength radiation entropy of each of the wavelengths; Obtaining the fitted and smoothed spectral emissivity based on the smoothed wavelength radiation entropy.

8. The system according to claim 7, wherein The high-order polynomial fitting method includes: for each wavelength, using the kernel function as a weight to perform local polynomial kernel regression to obtain a high-order polynomial as the regression function, and using the regression function to calculate the single-wavelength radiation entropy of each of the wavelengths as the smoothed wavelength radiation entropy; wherein, the local polynomial kernel regression includes: selecting a preset number of wavelengths adjacent to this wavelength, and performing polynomial fitting based on the kernel function within this range.

9. The system according to claim 8, wherein The coefficients of the high-order polynomial are calculated by using the following formula: θ = (X T K T KX) -1 X T K T KY wherein, θ is the coefficient vector of the polynomial function; X is the Vandermonde matrix with respect to the wavelength; K is the diagonalized kernel function matrix; and Y is the vector of the single-wavelength radiation entropy of each of the wavelengths.

10. The system according to claim 5, wherein The initial temperature of the first iteration is the maximum temperature T among the blackbody temperatures of the respective wavelengths max ; The initial spectral emissivities of each of the wavelengths in the first iteration are obtained by using the Planck blackbody radiation formula based on the maximum temperature.

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