ESTIMATION OF THE TEMPERATURE OF A STEEL PRODUCT

Abstract

The invention relates to a method for estimating the temperature of a steel product comprising a calibration step in which the intensities are recorded at 5 wavelengths ranging from 0.9 µm to 2.1 µm for various measurement conditions and the spectral attenuation coefficients are calculated, a measurement step in which the intensities are recorded at said wavelengths and the spectral attenuation coefficients are calculated for various temperatures, and a comparison step in which a probability test is performed to estimate the temperature of the steel product.

Description

ESTIMATION OF THE TEMPERATURE OF A STEEL PRODUCT This invention relates to a method for estimating the temperature of a steel product undergoing quenching treatment. The present method is particularly advantageous when water is present in the steel product. For example, in steelmaking, the claimed method can be applied during the secondary cooling of a continuous casting or at the exit table of a hot rolling mill. During the manufacturing of a steel strip, from its melting to its winding, the steel undergoes several cooling operations. These operations typically involve spraying water onto the steel. This can lead to the formation of a water film on the surface of the strip. Cooling operations typically involve models to regulate cooling power. These models use the belt temperature as input data. Therefore, to reliably control cooling, it is essential to accurately know the temperature during cooling operations. Pyrometers, which measure radiation intensities, are commonly used to measure the temperature of steel products. However, the measured radiation intensity is affected by the presence of a medium between the product and the pyrometer, such as a layer of water on the product. For example, when the steel surface and the surrounding environment are free of any disturbance, the accuracy is approximately ±10 °C. If there is water on the steel surface or mist between the steel and the pyrometer, the measurement error can reach 100 °C. When there is water on the steel surface and mist between the steel and the pyrometer, the measurement error can reach 200 °C. Consequently, there is a need to improve the accuracy of steel temperature measurement when there is water on the steel and / or mist between the band and the measuring device. EP 2 889 594 discloses a method for accurately measuring the surface temperature of steel during a water-cooling process. Radiation is recorded in the wavelength bands of 0.7 pm to 0.9 pm, 1.0 pm to 1.2 pm, and 1.6 pm to 1.8 pm. A pyrometer is used to measure the steel temperature. An optical glass is placed between the pyrometer and the steel at a predetermined distance. The optical glass is positioned so that, during the cooling process, the cooling water enters the space between the steel and the optical glass, resulting in a constant surface tension. The medium between the optical glass and the steel is thus known. The measured radiation intensity is then corrected using a coefficient related to the space between the steel and the optical glass.This allows for a reduction in temperature measurement error caused by the absorption or scattering of energy radiated by the water. The objective of the present invention is to provide a method that improves the accuracy of temperature measurement of a steel tape during a cooling operation. This is achieved by providing a method in accordance with any one of claims 1 to 4. CLn / nn / eznz / e / Yi Other features and advantages will become evident from the following detailed description of the invention. Figure 1 illustrates one modality of steps Ai to B.ii. of the claimed process. Figure 2 illustrates one type of water absorption spectrum as a function of wavelength. Figure 3 illustrates one type of water vapor absorption spectrum as a function of wavelength. Figure 4 illustrates one modality of several spectral attenuation coefficients Ccalib calculated in one calibration step. Figure 5 illustrates comparative results of the temperature of a steel strip measured by thermocouples and estimated by the claimed procedure. The invention relates to a method for estimating the Treal temperature of a steel product, having a temperature of 300 °C to 1600 °C, comprising: A. A calibration step comprising the steps of i. Measure the intensities (I) at 5 wavelengths (λ) between 0.9 pm and 2.1 pm, one of them being from 0.9 pm to 1.35 pm, another from 1.35 pm to 1.55 pm, another from 1.55 pm to 1.85 pm, another from 1.85 pm to 2.05 pm and another from 2.05 pm to 2.1 pm, using a sensor, of the radiation emitted by a reference of known temperature (Tref) under measurement conditions characterized by an emissivity of said reference (sref) and a transmittance of a medium between said reference and said sensor (oree), said reference being a steel product. i. Calculate a spectral attenuation coefficient Ccalib using said measured intensities (I) at said 5 wavelengths. Yo Ccalib —Dn T7 —£ref .aREF1refJ where Ρ(λ, Tref) is the spectral density of the electromagnetic radiation emitted by a black body in thermal equilibrium, based on Planck's Law, at a wavelength (λ) and a temperature (Tref), iii. Repeating steps i. and ii. for Ncalib different combinations of reference emissivity (sref) and transmittance of a medium between said reference and said sensor (oref) to obtain Ncalib spectral attenuation coefficients, Ncalib being an integer greater than 2, B. A measurement step comprising the steps of i. Measure the intensities of the radiation emitted by said steel product, I, at said 5 wavelengths (λ) between 0.9 pm and 2.1 pm, i. Calculation of the spectral attenuation coefficients Nt CcalculoTj, for temperatures Nt (Tj) between 300 °C and 1600 °C and for said 5 wavelengths, Nt being an integer between 2 and 1300, i CcÁLCULoTl=n[~, T¡',= £cálculox^cálculo CLn / nn / eznz / e / Yi > S κ c M a where *s P(λ, Tj) is the spectral density of the electromagnetic radiation emitted by a black body in thermal equilibrium, based on Planck's Law, at a wavelength ° (λ) and a temperature (Tref), C. A comparison step comprising the steps of i. Perform a probability test to find the most probable CcalculoTj among the Ccalib. i. Estimate the temperature of said steel product, Treal, as equal to the temperature Tj of said most probable CcalculoTj. The steps of the process are illustrated in Figure 1. The steel product can be any type of product, such as a strip, band, or slab. The temperature of the steel product is not known; however, depending on the process steps at which the measurement is taken, the expert in the field knows the temperature range within which it should fall. For example, in the quenching treatment of a steel strip after hot rolling, the temperature of the steel strip is typically between 300 °C and 1100 °C. In calibration step A.I., the intensities of the radiation emitted by the reference steel product can be measured by any suitable means. Preferably, they are measured with a hyperspectral camera. In calibration step Ai, the reference steel product preferably has a composition similar to that of the steel product whose temperature has been estimated. Even more preferably, the reference steel product has the same grade as the steel product being analyzed. In calibration step A.I., the temperature of the reference steel product can be measured by any means. Preferably, this temperature is measured using thermocouples. In calibration step A.ii., a spectral attenuation coefficient Ccalib can be calculated by dividing each of the recorded intensities I by P(A,Tj) at the measured temperature. Steps Ai and Aii are repeated for Ncalib multiple times, each time corresponding to new measurement conditions. The measurement conditions are defined by a combination of the reference emissivity (cref) and the transmittance of the medium between the reference and the sensor (oref). This allows obtaining several Ccalib values ​​for different measurement conditions. The higher the Ccalib value, the greater the accuracy of the estimate. In other words, steps i. and ii. of calibration step A. are repeated for different combinations of steel product emissivity (sref) and measurement condition transmittance (oref). sref varies depending on several factors, such as the temperature of the reference steel product, surface properties (such as the presence of oil), and oref depends on the medium between the sensor and the reference steel product, such as the thickness of a water layer on the reference steel product. However, it is not necessary to know the values ​​of sref and oref to calculate Ccalib. In measurement step Bi, the intensities emitted by the steel product are preferably measured using a hyperspectral camera. The wavelength at which the intensities are measured in step Bi is the same as in step Ai. In measurement step B.ii., the greater the number of temperatures (Nt) for which a spectral attenuation coefficient is calculated, the greater the accuracy of the estimate. Furthermore, in both the calibration and measurement steps, the measured intensities can be adjusted using a transfer function. Measuring the radiation intensities at these five wavelengths—from 0.9 pm to 1.35 pm, from 1.35 pm to 1.55 pm, from 1.55 pm to 1.85 pm, from 1.85 pm to 2.05 pm, and from 2.05 pm to 2.1 pm—allows us to describe the shape of the spectrum resulting from a combination of the product's emissivity and the medium's transmittance using a small number of intensities. In fact, within the 0.9 pm to 2.1 pm range, the absorption spectrum of water, shown in Figure 1, exhibits two peaks: one from 1.35 pm to 1.55 pm and another from 1.85 pm to 2.05 pm. In the comparison step C., a probability test is performed to find the most probable CcalculatedTj among the Ccalib. Any method that allows finding the most probable CcalculatedTj among the Ccalib can be used. This method allows for improved accuracy in estimating the temperature of a steel product because the estimate takes into account the influence of the measurement condition, such as the presence of water in the steel product. Preferably, this cooling treatment is carried out during or after hot rolling, and the steel product has a temperature of 300 °C to 1100 °C, where in step B, Tj ranges between 300 °C and 1100 °C. This cooling is usually carried out on an exit table. Preferably, said cooling treatment is carried out during casting or in continuous casting and said steel product has a temperature of 800 °C to 1600 °C and where in step B, Tj ranges between 800 °C and 1600 °C. Preferably, in steps A)¡. and B)¡., the radiation intensities of 8 wavelengths (λ) range from 0.9 pm to 2.1 pm, where one is from 0.9 pm to 1.11 pm, one is from 1.11 pm to 1.15 pm, one is from 1.15 pm to 1.35 pm, one is from 1.35 pm to 1.55 pm, one is from 1.55 pm to 1.85 pm, one is from 1.85 pm to 2.05 pm, one is from 2.05 pm to 2.07 pm and one is from 2.07 pm to 2.1 pm are measured and in steps A)¡. and B)¡¡., the spectral attenuation coefficients for said 8 wavelengths are calculated. Measuring the radiation intensities at these eight wavelengths improves measurement accuracy when a medium, such as vapor, is present between the steel product and the sensor. The intervals from 1.11 pm to 1.15 pm and from 2.05 pm to 2.07 pm correspond to peaks in the vapor absorption spectrum, as illustrated in Figure 2. Furthermore, these two peaks do not correspond to the vapor absorption spectrum.Furthermore, those two peaks do not coincide with the peaks of the water absorption spectrum. Preferably, in steps A)i. and B)ii., the radiation intensities are measured at 5 additional wavelengths between 0.9 pm and 2.1 pm, and in steps A)ii. and B)ii., the spectral attenuation coefficients are calculated for these 8 wavelengths and these 5 additional wavelengths. Preferably, the 13 wavelengths are evenly distributed across these ranges, meaning that the 13 wavelengths are spaced at intervals of 0.1 pm (0.9 pm, 1.0 pm, CLn / nn / eznz / e / Yi ...., 2.0 μιη, 2.1 μηι). Preferably, in steps A)i. and B)i., the radiation intensities are measured at 42 additional wavelengths between 0.9 pm and 2.1 pm and, in steps A)i. and B)i., the spectral attenuation coefficients are calculated for said 8 wavelengths and said 42 additional wavelengths. Preferably, in steps A)i. and B)i., the radiation intensities are measured at 92 additional wavelengths between 0.9 pm and 2.1 pm and, in steps A)ii. and B)ii., the spectral attenuation coefficients are calculated for these 8 wavelengths and 92 additional wavelengths. Preferably, Ncalib is an integer from 2 to 1000 and preferably from 20 to 1000. Preferably, in step C)i., the probability test comprises a dimensionality reduction of said Ccalib that defines the principal components. Even more preferably, in step C)i., the dimensionality reduction is performed using a principal component analysis. Preferably, in step C)¡., the probability test comprises projecting said Ccalib onto a probabilistic model. Even more preferably, in step C)¡., said probabilistic model is a Gaussian mixture model. MODALITY OF THE INVENTION To evaluate the accuracy of the claimed method, the temperature of a steel strip being cooled on an output table was measured using a thermocouple and estimated using the present method. A. Calibration step During the calibration step, a hyperspectral camera recorded the intensity of the radiation emitted by a cooled steel strip on an output table. Specifically, intensities were recorded at 256 wavelengths between 1.1 pm and 2.1 pm. These 256 wavelengths were uniformly distributed within this range. The temperature of the steel strip was measured using thermocouples. The calibration stages comprised six tests lasting between 5 and 15 minutes, during which radiation intensities were measured between 10 and 100 times per second. Thousands of measurement conditions were thus recorded. These tests were performed during cooling (in the presence of droplets, mist, and water) and before / after cooling (without water or mist), and for steel tapes with varying levels of oxidation. Next, several spectral attenuation coefficients (Ccalib) were calculated using the spectral density of the electromagnetic radiation emitted by a blackbody in thermal equilibrium, the temperature measured by thermocouples, and the hyperspectral camera transfer function. Each Ccalib had 256 values, one for each of the 256 wavelengths. The Ccalib values ​​are plotted in Figure 4. B. Measurement During the measurement step, a hyperspectral camera recorded the intensity of the radiation emitted by a cooled steel strip on an output table. More precisely, the following were recorded: CLn / nn / eznz / e / Yi intensities, at the same 256 wavelengths as in the calibration step. In addition, 261 temperatures, ranging from 300 °C to 1600 °C, have been defined as possible temperatures for the measured steel tape, so Nt = 261. These temperatures were spaced at intervals of 5 °C: (300 °C, 305 °C, 310 °C ... 1595 °C, 1600 °C). Next, the radiation intensities measured at these 256 wavelengths were divided by the value of Planck's law and multiplied by the transfer function for each of the 261 temperatures defined above. This resulted in the calculation of 261 spectral attenuation coefficients CcalculatedTj. Each of these 261 spectral attenuation coefficients had 256 values, one for each measured wavelength, and an associated temperature. C. Comparison The probability test for this realization comprises 10 steps. 1) A principal component analysis (PCA) is performed on all Ccalib spectral attenuation coefficients obtained during the calibration step to obtain 3 PCA principal components (PCi, PC2, PC3). Then, each Ccalib in the database is approximated using these three principal components. 2) The spectral attenuation coefficients are projected onto a PCA space defined by the 3 principal components defined above. 3) The density of points in the PCA space from step 2) is projected onto a Gaussian mixture model. 4) Each of said 261 CcalculatedTj is projected into the PCA space defined by the 3 principal components previously defined. 5) For each of the 261 CcalculatedTj, an approximate spectral attenuation coefficient is reconstructed from its coordinates in the PCA space defined in 4) and a first probability factor (Likel) is defined by comparing the original spectral attenuation and its reconstruction from the PCA coefficients. 6) Each of these 261 CcalculatedTj is projected onto the Gaussian mixture model defined in 3) and a second probability factor (Like2) is determined. Like2 represents the local density of the learning data projected onto the PCA space. Therefore, two probabilities (Likel and Like2) are associated with each of the 261 CcalculatedTj. 7) Next, the product of Likel and Like2 is calculated for each of said 261 CcalculatedTj. Finally, the temperature associated with the CcalculatedTj that maximizes the product of 7) is defined as the temperature of the steel strip. Figure 5 shows the comparative results of the temperature obtained through thermocouple measurements and through the intended estimation. The dotted line represents the temperature estimated using the method described above, while the solid line represents the temperature measured by thermocouples. It is clear that the temperature obtained using this method is reliable.

Claims

1. A method for estimating the Treal temperature of a steel product, having a temperature of 300 °C to 1600 °C, comprising: A. A calibration step comprising the steps of i. measuring the intensities (I), at 5 wavelengths (λ) between 0.9 pm and 2.1 pm, one of them being from 0.9 pm to 1.35 pm, another from 1.35 pm to 1.55 pm, another from 1.55 pm to 1.85 pm, another from 1.85 pm to 2.05 pm and another from 2.05 pm to 2.1 pm, by means of a sensor, of the radiation emitted by a reference of known temperature (Tref) under measurement conditions characterized by an emissivity of said reference (cref) and a transmittance of a medium between said reference and said sensor (oref), said reference being a steel product, i. Calculate a spectral attenuation coefficient Ccalib using these measured intensities (I) at these 5 wavelengths, I Ccalib — nn τ λ — £ref .aREF “ 'Ά 'refJ where Ρ(λ, Tref) is the spectral density of the electromagnetic radiation emitted by a black body in thermal equilibrium, based on Planck's Law, at a wavelength (λ) and a temperature (Tref), ii. Repeating steps i. and i.i. for different combinations of reference emissivity (cree) and transmittance of a medium between said reference and said sensor (oref) to obtain spectral attenuation coefficients Ncalib, Ncalib being an integer greater than 2, B. A measurement step comprising the steps of i. Measuring intensities of the radiation emitted by said steel product, I, at said wavelengths (λ) between 0.9 pm and 2.1 pm, i.i.Calculation of the spectral attenuation coefficients Nt CcalculoTj, for temperatures Nt (Tj) between 300 °C and 1600 °C and for said 5 wavelengths, Nt being an integer between 2 and 1300, I Ccálculu'í'Í — γρ — £cálculo x “cálculo” where ρ(λ, Tj) is the spectral density of the electromagnetic radiation emitted by a black body in thermal equilibrium, based on Planck's Law, at a wavelength (λ) and a temperature (Tref), C. A comparison step comprising the steps of i. Perform a probability test to find the most probable CcálculoTj among the Ccalib i. Estimate the temperature of said steel product, Treal, as equal to the temperature Tj of said CcálculoTj more likely.

2. The method according to claim 1, wherein said cooling treatment is carried out during or after hot rolling and said steel product has a temperature of 300 °C to 1100 °C and wherein in step B, Tj ranges from 800 °C to 1600 °C.

3. The method according to claim 1, wherein said cooling treatment is carried out during or after continuous melting and said steel product has a temperature of 800 °C to 1600 °C and wherein in step B, Tj ranges between 800 °C and 1600 °C.

4. The method according to any of claims 1 to 3, in steps A)i. and B)i., the radiation intensities of 8 wavelengths (λ) ranging from 0.9 pm to 2.1 pm, where one is from 0.9 pm to 1.11 pm, one is from 1.11 pm to 1.15 pm, one is from 1.15 pm to 1.35 pm, one is from 1.35 pm to 1.55 pm, one is from 1.55 pm to 1.85 pm, one is from 1.85 pm to 2.05 pm, one is from 2.05 pm to 2.07 pm and one is from 2.07 pm to 2.1 pm are measured and in steps A)i. and B)i., the spectral attenuation coefficients for said 8 wavelengths are calculated.

5. The method according to claim 4, wherein in steps A)i. and B)i., the radiation intensities are measured at 5 additional wavelengths between 0.9 pm and 2.1 pm and, in steps A)ii. and B)ii., the spectral attenuation coefficients are calculated for said 8 wavelengths and said 5 additional wavelengths.

6. The method according to claim 4, wherein in steps A)i. and B)i., the radiation intensities are measured at 42 additional wavelengths between 0.9 pm and 2.1 pm and, in steps A)i. and B)i., the spectral attenuation coefficients are calculated for said 8 wavelengths and said 42 additional wavelengths.

7. The method according to claim 4, wherein in steps A)i. and B)i., the radiation intensities are measured at 92 additional wavelengths between 0.9 pm and 2.1 pm and, in steps A)ii. and B)ii., the spectral attenuation coefficients are calculated for said 8 wavelengths and said 92 additional wavelengths.

8. The method according to any one of claims 1 to 7, wherein Ncalib is an integer from 2 to 1000 and preferably from 20 to 1000.

9. The method according to any of claims 1 to 8, wherein in step C)¡., the probability test comprises a reduction of the dimensionality of said Ccalib that defines the principal components.

10. In the method according to claim 9, in step C)¡., the dimensionality reduction is performed using a principal component analysis.

11. The method according to any of claims 1 to 10, wherein in step C)¡., the probability test comprises projecting said Ccalib onto a probabilistic model.

12. The method according to claim 11, wherein in step C)i., said probabilistic model is a Gaussian mixture model

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