Three-dimensional characterization method and system for semi-macrosegregation spots of continuous casting billet

Abstract

The invention discloses a continuous casting billet semi-macrosegregation spot three-dimensional characterization method and system. The method comprises the steps that S1, a continuous casting billet sample is subjected to multi-layer planing and grinding and acid pickling corrosion, and continuous casting billet semi-macrosegregation spots are obtained; step S2, acquiring a color picture of the semi-macrosegregation spots of the continuous casting billet by using an optical microscope, preprocessing the picture to obtain a two-dimensional morphology of the semi-macrosegregation spots, and storing the two-dimensional morphology of the semi-macrosegregation spots; and S3, reconstructing the stored two-dimensional morphology data of the semi-macrosegregation spots to obtain the three-dimensional representation of the semi-macrosegregation spots of the continuous casting billet. According to the method, the semi-macrosegregation spot two-dimensional distribution characteristics are obtained through planing, grinding and acid pickling corrosion of a continuous casting billet sample and through light microscope detection. The sample is subjected to multi-layer planing and grinding and acid pickling corrosion, and semi-macrosegregation spot evolution characteristics at different depth positions of the sample are obtained. And representing the three-dimensional distribution characteristics of the semi-macrosegregation spots through gray value processing and data reconstruction of the semi-macrosegregation spots.

Description

Technical Field

[0001] The invention relates to the technical field of steel continuous casting production, and in particular to a three-dimensional characterization method and system for semi-macroscopic segregation spots of a continuous casting billet. Background Art

[0002] During the continuous casting solidification process, under the cooling effect of the copper plate of the crystallizer and the water spray in the secondary cooling zone, columnar crystals grow from the surface of the continuous casting billet to the liquid phase hole. As the melt temperature decreases, equiaxed grains nucleate in the liquid phase hole and gradually grow. Due to the difference in solubility of solute elements in the solid phase and the liquid phase, as the continuous casting solidification proceeds, the solute elements are continuously discharged from the solid phase, and the liquid phase enriched between the dendrites forms microscopic segregation defects. Under the action of thermal buoyancy flow, grain precipitation, billet shell deformation, etc., the solute-enriched liquid phase and the poor solid phase move relative to each other, forming large-scale semi-macro segregation and macro segregation defects. Microscopic segregation can be basically eliminated during the heat treatment of the continuous casting billet, and macro segregation can be controlled by mechanical pressing, electromagnetic stirring, and low superheat casting technology, while semi-macro segregation defects cannot be controlled yet. The semi-macro segregation spots of continuous casting billets are mainly located between the dendrite arms. During the heating process, the alloy solute elements cannot be diffused evenly, especially the substitutional atoms such as Mn and Cr, which have a low diffusion rate and a large semi-macro segregation range of elements, which cannot be evenly distributed during the effective heat treatment process. Especially for special steels with high solute content, the segregation spots are serious during the large-section continuous casting production process. During the rolling and heat treatment process, the semi-macro segregation defects cannot be completely eliminated and are inherited to the core of the rolled material. By increasing the rolling cooling rate and reducing the curling temperature of the rolled plate, the banded structure defects can be reduced to a certain extent. However, during the high-temperature tempering process of the rolled material, the banded structure reappears, seriously affecting the mechanical properties and quality stability of the steel.

[0003] Therefore, it is necessary to study the degree of semi-macro segregation spots and the influence of external fields on semi-macro segregation defects in order to reduce the grade of banded structure. At present, the characterization of semi-macro segregation in continuous casting billets is generally carried out by pickling and corrosion methods, and the number and area of ​​segregation spots are statistically analyzed to obtain the distribution characteristics of semi-macro segregation. However, semi-macro segregation defects present a three-dimensional distribution in the continuous casting billet. Currently, only the two-dimensional morphology of semi-macro segregation spots can be obtained through sample planing and pickling and corrosion, and the three-dimensional distribution characteristics of segregation cannot be fully obtained. Summary of the invention

[0004] The present invention proposes a method for reconstructing the three-dimensional structure of semi-macro segregation spots of continuous casting billets. The morphology and evolution law of semi-segregation spots at different depths of the sample are obtained through multi-layer planing and pickling corrosion of the sample. The three-dimensional distribution characteristics of the semi-macro segregation spots are quantitatively obtained through two-dimensional gray value processing and data reconstruction, laying a foundation for the control of semi-macro segregation of continuous casting billets. The method includes:

[0005] Step S1, performing multi-layer planing and pickling corrosion on the continuous casting billet sample to obtain semi-macro segregation spots of the continuous casting billet;

[0006] Step S2, using an optical microscope to obtain a color photograph of the semi-macro segregation spots of the continuous casting billet, preprocessing the photograph to obtain a two-dimensional morphology of the semi-macro segregation spots and storing the same;

[0007] Step S3, reconstructing the stored two-dimensional morphological data of the semi-macro segregation spots to obtain a three-dimensional representation of the semi-macro segregation spots of the continuous casting billet.

[0008] Optionally, in step S1, the multi-layer planing is performed using a manual sample grinding machine, and the planing depth is 20 to 30 μm each time. The thickness Z is recorded based on the planing depth. i , i is the number of planing times.

[0009] Optionally, in step S1, the pickling corrosion uses a saturated picric acid corrosion solution and the corrosion is carried out at 80° C. for 20 to 30 seconds.

[0010] Optionally, in step S2, the preprocessing is to grayscale the color photo of the semi-macro segregation spots of the continuous casting billet, randomly select any planing depth Z i and two adjacent layers Z i+1 and Z i+2 The corresponding gray value α i , α i+1 , α i+2 Perform data fitting:

[0011]

[0012] Based on several fitting results, the gray value files at different planing depth Z positions are obtained.

[0013] Optionally, in step S3, the data reconstruction process specifically includes:

[0014] Extract two-dimensional gray value data from the grayscale image;

[0015] Reconstructing the three-dimensional morphology of the segregation spots based on the two-dimensional gray value data,

[0016] The three-dimensional characterization of the semi-macroscopic segregation spots in the continuous casting billet is characterized based on the equivalent diameter, sphericity and number density of the segregation spots in the three-dimensional morphology.

[0017] The present invention also discloses a three-dimensional characterization system for semi-macro segregation spots of continuous casting billets, the system comprising:

[0018] The sample spot extraction module is used to perform multi-layer planing and pickling corrosion on the continuous casting billet sample to obtain the semi-macro segregation spots of the continuous casting billet;

[0019] An image preprocessing module, used for obtaining color photos of the semi-macro segregation spots of the continuous casting billet using an optical microscope, preprocessing the photos to obtain and store the two-dimensional morphology of the semi-macro segregation spots;

[0020] The spot characterization module is used to reconstruct the stored two-dimensional morphological data of the semi-macro segregation spots to obtain a three-dimensional characterization of the semi-macro segregation spots of the continuous casting billet.

[0021] Optionally, multi-layer planing is performed using a manual grinding machine, with each planing depth of 20 to 30 μm, and the thickness Z is recorded based on the planing depth. i , i is the number of planing times.

[0022] Optionally, the pickling corrosion uses a saturated picric acid corrosion solution and the corrosion is carried out at 80° C. for 20 to 30 seconds.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] The invention is characterized in that: the two-dimensional distribution characteristics of the semi-macro segregation spots are obtained by planing and pickling the continuous casting billet sample, and the light microscope is used for detection. The sample is subjected to multi-layer planing and pickling to obtain the evolution characteristics of the semi-macro segregation spots at different depths of the sample. The three-dimensional distribution characteristics of the semi-macro segregation spots are characterized by gray value processing and data reconstruction of the semi-macro segregation spots. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0026] Figure 1 This is a schematic diagram of sampling a continuous casting slab according to an embodiment of the present invention;

[0027] Figure 2 This is a picture of semi-macro segregation spot corrosion in an embodiment of the present invention;

[0028] Figure 3 A three-dimensional structural diagram of a single segregation spot in an embodiment of the present invention;

[0029] Figure 4 A three-dimensional structure diagram of semi-macro segregation spots of a sample according to an embodiment of the present invention;

[0030] Figure 5 This is a method step diagram of a three-dimensional characterization method for semi-macro segregation spots of a continuous casting slab according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0033] Embodiment 1

[0034] A three-dimensional characterization method for semi-macro segregation spots in continuous casting billets, such as Figure 5 As shown, the method includes:

[0035] Step S1, multi-layer planing and pickling corrosion are performed on the continuous casting billet sample to obtain semi-macro segregation spots of the continuous casting billet. The multi-layer planing and grinding adopts a manual sample grinding machine, and the planing depth of each time is 20-30 μm. The pickling corrosion adopts a saturated picric acid corrosion liquid, and the corrosion is carried out at 80° C. for 20-30 seconds.

[0036] Step S2, using an optical microscope to obtain a color photo of the semi-macro segregation spots of the continuous casting billet, pre-processing the photo to obtain a two-dimensional morphology of the semi-macro segregation spots and storing it. Grayscale processing, characterized in that the color semi-macro segregation spot picture is converted into a black and white segregation spot picture using Image-J software.

[0037] During the continuous casting process, samples were cut, planed, and pickled, and then tested using an optical microscope to obtain the two-dimensional morphology and distribution characteristics of the semi-macro segregation spots. The specific process is as follows:

[0038] Step 21: Based on the color image of the semi-macro segregation spots obtained by the optical microscope, Image-J software is used to convert the color image into a black and white image and perform grayscale value processing.

[0039] Step 22: Use Python software to write a processing program to convert the black and white semi-macro segregation spot image into gray value data, and save it in an Excel file to store the gray value of each pixel node.

[0040] Step 23: Plane and grind the sample layer by layer to a thickness of 20 to 30 μm, and perform pickling and etching and optical microscopy observation to obtain the two-dimensional morphology of the semi-macro segregation spots under the sample thickness condition. In this example, the planing times are 15 times, and the total planing thickness reaches 410 μm.

[0041] Step 24: Use Image-J software and Python program to convert the semi-macro segregation spots of different thicknesses of the sample into gray value files, where the cumulative thickness of the planed layer is recorded as Z i coordinate.

[0042] Step 25: Extract three adjacent planing layers Z i , Z i+1 , Z i+2 Gray value data α i , α i+1 , α i+2 , and a quadratic polynomial fitting is performed, where the data fitting formula (1) is shown. The gray value α under different thickness Z coordinate conditions between adjacent layers is calculated according to the formula.

[0043]

[0044] Step 26: By fitting and processing the data of different planed layers, the grayscale value data files of the samples with different thicknesses in the Z direction are obtained, and the data are arranged in increasing order from the X, Y, and Z coordinate values, and saved in the dat data.

[0045] Step 27: Import the dat data file of the semi-macro segregation spots through Tecplot software to obtain the three-dimensional morphology of the semi-macro segregation spots, such as Figure 3 shown.

[0046] Step S3, reconstructing the stored two-dimensional morphological data of the semi-macro segregation spots to obtain a three-dimensional representation of the semi-macro segregation spots of the continuous casting billet. The data reconstruction process specifically includes: extracting two-dimensional gray value data from the grayed image;

[0047] Reconstructing the three-dimensional morphology of the segregation spots based on the two-dimensional gray value data,

[0048] The three-dimensional characterization of the semi-macroscopic segregation spots in the continuous casting billet is characterized based on the equivalent diameter, sphericity and number density of the segregation spots in the three-dimensional morphology.

[0049] The three-dimensional morphology of the semi-macro segregation spots was obtained by Tecplot software, and the equivalent diameter, sphericity, number density and other data of the segregation spots were analyzed to quantitatively characterize the distribution characteristics of the semi-macro segregation spots in the continuous casting billet.

[0050] Embodiment 2

[0051] A three-dimensional characterization system for semi-macro segregation spots of continuous casting billets, the system comprising:

[0052] The sample spot extraction module is used to perform multi-layer planing and pickling corrosion on the continuous casting billet sample to obtain the semi-macro segregation spots of the continuous casting billet.

[0053] The multi-layer planing and grinding was performed with a manual sample grinder, and the depth of each planing and grinding was 20 to 30 μm. The pickling and etching was performed with a saturated picric acid etching solution, and the etching was performed at 80°C for 20 to 30 seconds.

[0054] The image preprocessing module is used to obtain color photos of the semi-macro segregation spots of the continuous casting billet using an optical microscope, preprocess the photos, obtain the two-dimensional morphology of the semi-macro segregation spots and store them.

[0055] Grayscale processing is characterized by using Image-J software to convert the color semi-macro segregation spot image into a black and white segregation spot image.

[0056] During the continuous casting process, samples were cut, planed, and pickled, and then tested using an optical microscope to obtain the two-dimensional morphology and distribution characteristics of the semi-macro segregation spots. The specific process is as follows:

[0057] According to the color images of semi-macroscopic segregation spots obtained by optical microscopy, the color images were converted into black and white images using Image-J software and gray value processing was performed.

[0058] The processing program was written using Python software to convert the black and white semi-macro segregation spot images into grayscale value data, which were saved in Excel files to store the grayscale value of each pixel node.

[0059] The sample was planed layer by layer to a thickness of 20 to 30 μm, and pickling and etching were performed and optical microscopy was performed to obtain the two-dimensional morphology of the semi-macro segregation spots under the sample thickness condition. In this example, the planing was performed 15 times, and the total planing thickness reached 410 μm.

[0060] Image-J software and Python program were used to convert the semi-macro segregation spots of different thicknesses into grayscale value files, in which the cumulative thickness of the planed layer was recorded as Z i coordinate.

[0061] Extract three adjacent planing layers Z i , Z i+1 , Z i+2 Gray value data α i , α i+1 , α i+2 , and a quadratic polynomial fitting is performed, where the data fitting formula (1) is shown. The gray value α under different thickness Z coordinate conditions between adjacent layers is calculated according to the formula.

[0062]

[0063] By fitting and processing the data of different planed layers, the grayscale value data files of the samples with different thicknesses in the Z direction are obtained, and the data are arranged in increasing order from the X, Y, and Z coordinate values, and saved in the dat data.

[0064] The dat data file of the semi-macro segregation spots was imported into the Tecplot software to obtain the three-dimensional morphology of the semi-macro segregation spots.

[0065] The spot characterization module is used to reconstruct the stored two-dimensional morphological data of the semi-macro segregation spots to obtain the three-dimensional characterization of the semi-macro segregation spots of the continuous casting billet. The data reconstruction process specifically includes: extracting two-dimensional gray value data from the grayscale image;

[0066] Reconstructing the three-dimensional morphology of the segregation spots based on the two-dimensional gray value data,

[0067] The three-dimensional characterization of the semi-macroscopic segregation spots in the continuous casting billet is characterized based on the equivalent diameter, sphericity and number density of the segregation spots in the three-dimensional morphology.

[0068] The three-dimensional morphology of the semi-macro segregation spots was obtained by Tecplot software, and the equivalent diameter, sphericity, number density and other data of the segregation spots were analyzed to quantitatively characterize the distribution characteristics of the semi-macro segregation spots in the continuous casting billet.

[0069] Embodiment 3

[0070] This example takes the continuous casting production of E355 pipeline steel slab as an example. The cross-sectional size of the continuous casting slab of this steel type is 230mm×1350mm. The cross section of the continuous casting slab is flame cut and a sample is taken at a quarter of the thickness in the middle of the wide surface of the continuous casting slab. Figure 1 As shown. The three-dimensional reconstruction and characterization of semi-macro segregation spots of continuous casting slabs are achieved through the following steps;

[0071] 1. Cut the sample of the continuous casting billet, grind it with sandpaper, and then pickle it. The pickle is saturated with picric acid at 80℃ for 30s. Use an optical microscope to observe the two-dimensional morphology of the semi-macro segregation spots of the sample, such as Figure 2 As shown. Figure 2 The semi-macro-segregation spots in the black circle were subjected to data processing and characterization.

[0072] 2. The three-dimensional characterization of semi-macro segregation spots of continuous casting slabs is achieved by the following steps;

[0073] According to the color images of semi-macroscopic segregation spots obtained by optical microscopy, the color images were converted into black and white images using Image-J software and grayscale value processing was performed.

[0074] Python software was used to write a processing program to convert the black and white semi-macro segregation spot images into grayscale data and save them in Excel files to store the grayscale values ​​of each pixel node. In the saved data, the horizontal direction is the X coordinate and the vertical direction is the Y coordinate.

[0075] The sample was planed layer by layer, with a planing depth of 20 to 30 μm, and pickling and etching were performed and optical microscopy was observed to obtain the two-dimensional morphology of the semi-macro segregation spots under the sample depth condition. In this example, the planing times were 15 times, and the planing depth reached 410 μm.

[0076] Image-J software and Python program were used to convert the semi-macro segregation spots at different depths of the sample into grayscale value files, where the depth is the Z coordinate.

[0077] According to the gray value data files of semi-macro segregation spots at different depths of the sample, the data are arranged in sequence from the X, Y, and Z coordinate values ​​and saved in the dat data.

[0078] Import the dat data file of the semi-macro segregation spots through Tecplot software to obtain the three-dimensional morphology of the semi-macro segregation spots, such as Figure 3 shown.

[0079] 3. The three-dimensional morphology of the semi-macro segregation spots was drawn using Tecplot software, and the characteristics of the semi-macro segregation spots were analyzed. The equivalent diameter of the semi-macro segregation spots at a quarter of the thickness of the ingot was 181.1 μm, and the sphericity of the segregation spots was 0.71. Figure 3 .

[0080] 4. Through the overall processing of the sample at this position, the sample width is 2.02mm, the sample length is 1.46mm, the sample detection depth is 0.41mm, and the number density of semi-macro segregation spots is 15.3mm through detection and analysis. -3 ,like Figure 4 shown.

[0081] The embodiments described above are only descriptions of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A three-dimensional characterization method for semi-macro segregation spots of continuous casting billets, characterized in that: The method comprises: Step S1, performing multi-layer planing and pickling corrosion on the continuous casting billet sample to obtain semi-macro segregation spots of the continuous casting billet; Step S2, using an optical microscope to obtain a color photograph of the semi-macro segregation spots of the continuous casting billet, preprocessing the photograph to obtain a two-dimensional morphology of the semi-macro segregation spots and storing the same; Step S3, reconstructing the stored two-dimensional morphological data of the semi-macro segregation spots to obtain a three-dimensional representation of the semi-macro segregation spots of the continuous casting billet.

2. The three-dimensional characterization method for semi-macro segregation spots of continuous casting billet according to claim 1 is characterized in that: In step S1, the multi-layer planing is performed using a manual sample grinding machine, and the planing depth is 20 to 30 μm each time. The thickness Z is recorded based on the planing depth. i , i is the number of planing times.

3. The three-dimensional characterization method of semi-macro segregation spots of continuous casting billet according to claim 2, characterized in that: In step S1, the pickling and etching is carried out using a saturated picric acid etching solution at 80° C. for 20 to 30 seconds.

4. The three-dimensional characterization method for semi-macro segregation spots of continuous casting billet according to claim 1, characterized in that: In the step S2, the pre-processing is to grayscale the color photo of the semi-macro segregation spots of the continuous casting billet, randomly select any planing depth Z i and two adjacent layers Z i+1 and Z i+2 The corresponding gray value α i , α i+1 , α i+2 Perform data fitting: Based on several fitting results, the gray value files at different planing depth Z positions are obtained.

5. The three-dimensional characterization method of semi-macro segregation spots of continuous casting billet according to claim 1, characterized in that: In step S3, the data reconstruction process specifically includes: Extract two-dimensional gray value data from the grayscale image; Reconstructing the three-dimensional morphology of the segregation spots based on the two-dimensional gray value data, The three-dimensional characterization of the semi-macroscopic segregation spots in the continuous casting billet is characterized based on the equivalent diameter, sphericity and number density of the segregation spots in the three-dimensional morphology.

6. A three-dimensional characterization system for semi-macro segregation spots of continuous casting slabs, the system being used to implement the method according to any one of claims 1 to 5, characterized in that: The system includes: The sample spot extraction module is used to perform multi-layer planing and pickling corrosion on the continuous casting billet sample to obtain the semi-macro segregation spots of the continuous casting billet; An image preprocessing module, used for obtaining color photos of the semi-macro segregation spots of the continuous casting billet using an optical microscope, preprocessing the photos to obtain and store the two-dimensional morphology of the semi-macro segregation spots; The spot characterization module is used to reconstruct the stored two-dimensional morphological data of the semi-macro segregation spots to obtain a three-dimensional characterization of the semi-macro segregation spots of the continuous casting billet.

7. The continuous casting slab semi-macro segregation spot three-dimensional characterization system according to claim 6, characterized in that: The multi-layer planing was performed using a manual grinding machine. The planing depth was 20 to 30 μm each time. The thickness Z was recorded based on the planing depth. i , i is the number of planing times.

8. The continuous casting slab semi-macro segregation spot three-dimensional characterization system according to claim 6, characterized in that: The pickling corrosion uses a saturated picric acid corrosion solution and corrodes at 80°C for 20 to 30 seconds.

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