A method and medium for thin gauge high strength steel quenching plate shape characterization and defect analysis determination
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 武汉钢铁有限公司
- Filing Date
- 2026-04-23
- Publication Date
- 2026-06-23
Smart Images
Figure CN122265265A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of metallurgical manufacturing technology, specifically to a method and medium for characterizing the shape and analyzing and judging defects in thin-gauge high-strength steel quenched plates. Background Technology
[0002] Thin-gauge high-strength steel plates are primarily produced through heat treatment (quenching and tempering) to achieve high strength. They are widely used in the manufacturing of large-scale engineering machinery and special-purpose vehicles, where the consistency of overall plate shape quality is crucial. In actual quenching production, due to minute inhomogeneities, thin-gauge steel plates undergo complex shape changes under the influence of multiple physical fields, resulting in various wavy defects after cooling, such as head and tail warping defects, edge (center) wavy defects, and central transverse bending defects. The plate shape exhibits different characteristics and distributions at the head, middle, and tail. To efficiently adjust the plate shape through process optimization, a quantitative evaluation of the thin-gauge steel plate's shape is essential.
[0003] Currently, some heat treatment sites are equipped with high-precision laser non-contact shape analyzers that can detect the overall shape of steel plates. However, these analyzers only display the shape in the form of three-dimensional images, shape cloud maps, and cross-sectional contour images. They lack quantitative characterization methods for the shape characteristics of different parts of the steel plate, making it difficult to effectively calculate the adjustment effect of process parameters. They cannot establish a correlation between specific shape defects and processes, resulting in unsatisfactory parameter adjustment effects. This leads to repeated manual process adjustments, affecting the product qualification rate of the production line and causing quality complaints from downstream users.
[0004] Therefore, it is necessary to systematically design a method for characterizing and analyzing the defects of thin-gauge ultra-high-strength steel plates, and establish a plate shape characterization and evaluation method covering the entire length of the steel plate to fully characterize the overall and local plate shape conditions. Summary of the Invention
[0005] To overcome the shortcomings of existing methods for evaluating the shape of quenched thin-gauge high-strength steel, which rely on qualitative observation, lack zonal quantitative characterization, and cannot automatically determine defect types, this paper provides a complete method for extracting shape features, calculating feature values, and automatically determining defects based on three-dimensional data from a shape analyzer. This method enables quantitative, refined, and automated evaluation of quenched plate shape.
[0006] In a first aspect, the present invention provides a method for characterizing the shape and analyzing and determining defects in thin-gauge high-strength steel quenched plates, including: The surface three-dimensional contour data of the steel plate after quenching is acquired online to form a plate height dataset containing the length direction coordinates, width direction coordinates and corresponding height values of the steel plate. The plate height dataset is divided into regions according to the length and width of the steel plate, at least into a head region, a tail region, a left side region, a right side region, and a middle region; Calculate the head warp height of the head region, the tail warp height of the tail region, the C-warp amplitude value of the middle region, and the wave-shaped characteristic values of the left side region, the right side region, and the middle region, respectively. The calculated feature values are compared with the preset corresponding defect judgment thresholds to determine the plate shape quality and main defect types of the steel plate.
[0007] In some instances, the plate shape height dataset is derived from plate shape gauge scan data at the quenching machine exit, which is stored in a three-dimensional data format containing length direction coordinates, width direction coordinates, and height values.
[0008] In some instances, the plate height dataset is divided into regions along the length and width of the steel plate, at least into a head region, a tail region, a left side region, a right side region, and a middle region, including: Head region: The region extending inward along the length direction from the edge of the steel plate head within a first preset distance; Tail region: The region extending inward along the length direction from the tail edge of the steel plate within a second preset distance; Left side region: Within the remaining length after removing the head and tail regions, the region extends inward along the width direction from the left edge of the steel plate at a third preset distance; Right side region: Within the remaining length after removing the head and tail regions, the region extends inward along the width direction from the right edge of the steel plate at a fourth preset distance; Central region: The region remaining after removing the head region, tail region, left side region, and right side region.
[0009] In some instances, the first preset distance is 1m, the second preset distance is 1m, the third preset distance is 0.2m, and the fourth preset distance is 0.2m.
[0010] In some instances, the head warp height and tail warp height are calculated as follows: For each column of data in the head or tail region, the column contains multiple data points distributed along the length of the steel plate. The coordinates of each data point are (yi, zi), where yi is the length direction coordinate and zi is the height value. The least squares method is used to fit a straight line to all data points in the column to obtain the intercept bi of the fitted line. The average of the intercepts bi calculated for all columns in the region is denoted as average(bi). Then the warping height h in this region is equal to average(bi) - thickness, where thickness is the steel plate thickness specification correction value. When h is positive, it indicates an upward curve; when h is negative, it indicates a downward curve.
[0011] In some instances, the C-curvature value is calculated as follows: For each row of data in the middle region, the row of data corresponds to a fixed position along the length of the steel plate. Take the left, right and middle data points of the row, and record their height values as zleft, zright and zmid respectively. Calculate the C-curve value ci = zmid - (zleft + zright) / 2 for the row. The average value of Cbend is calculated as average(ci) for all rows in the central region. When Cbend is positive, it indicates a downward C-curve; when Cbend is negative, it indicates an upward C-curve.
[0012] In some instances, the method for calculating the wave-shaped eigenvalues is as follows: Select a column of data along the length of the steel plate at the location to be calculated. This column of data contains multiple data points distributed along the length. The distance between adjacent data points is calculated as a straight line distance using the Pythagorean theorem. The actual curve length L is obtained by summing the straight line distances between all adjacent data points. Calculate the projected straight-line distance L0 between the first and last data points in this column of data; Then the wave-shaped characteristic value at this position is IU = (L - L0) / L0 × 10 5 ; The wave-shaped feature values include, but are not limited to: left side IU, right side IU, left quarter width IU, right quarter width IU, and middle IU.
[0013] In some instances, the defect determination threshold is preset based on at least one of the following factors: steel type, thickness specification, width specification, and user plate shape acceptance criteria.
[0014] In some instances, the method for determining the defect determination threshold includes at least one of the following: Directly cite the limit requirements for plate unevenness in national standards, industry standards, or enterprise standards; Statistical calculations were performed based on the shape characteristic values of historical qualified board samples, and the mean ± k times the standard deviation was taken as the threshold, where k is a preset coefficient; The plate shape acceptance criteria specified in the downstream user's technical agreement are directly used as the threshold.
[0015] In some instances, the defect type determination is specifically as follows: If the head curvature height is greater than the head upturn threshold, it is determined that there is a head upturn defect; if the head curvature height is less than the head downturn threshold, it is determined that there is a head downturn defect. If the height of the tail warp is greater than the tail warp threshold, it is determined that there is a tail warp defect; if the height of the tail warp is less than the tail droop threshold, it is determined that there is a tail droop defect. If the C-curve amplitude value is greater than the upper C-curve threshold, it is determined that there is an upper C-curve defect; if the C-curve amplitude value is less than the lower C-curve threshold, it is determined that there is a lower C-curve defect. If the IU of the left side is greater than the left side wave threshold, then a left side wave defect is determined to exist; if the IU of the right side is greater than the right side wave threshold, then a right side wave defect is determined to exist; if the IU of the middle part is greater than the middle wave threshold, then a middle wave defect is determined to exist.
[0016] In a second aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any of the methods described above.
[0017] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects: (1) This invention addresses the problem of lack of effective characterization methods for the shape of quenched thin-gauge high-strength steel plates and the inability to accurately determine the defect types. By collecting measurement data from a high-precision plate shape instrument, the entire plate is divided into five regions (head, tail, left side, middle side, and right side) based on the shape characteristics of the quenched plate. By setting the plate shape characteristic calculation method and the defect type determination threshold, the complex plate shape characteristics are digitized, realizing high-precision characterization of the quenched plate shape characteristics and accurate determination of the defect types. This lays the foundation for high-precision and quantitative analysis for subsequent quenched plate shape optimization.
[0018] (2) The quenched plate shape was quantitatively characterized by partitioning: the steel plate was divided into five independent regions: head, tail, left side, right side and middle. The warping height, C-warping amplitude value and wave shape IU value were calculated respectively. This overcame the limitations of the traditional single overall flatness index and could accurately locate the area where the plate shape problem occurred.
[0019] (3) A clear mapping relationship between plate shape features and defect types has been established: by setting physical thresholds for each feature value, continuous calculation results are mapped to discrete defect type judgments (such as upturn / downturn, up C-curve / down C-curve, edge wave / middle wave, etc.), realizing automated judgment of plate shape quality and reducing the difference of subjective human judgment.
[0020] (4) Provides a quantitative basis for process parameter optimization: The quantitative feature value output by this invention can be directly correlated with quenching process parameters (such as water ratio, roller speed, nozzle pressure distribution, etc.) for correlation analysis and regression modeling, so that the plate shape adjustment is upgraded from "experience trial and error" to "data-driven" precise control, which can significantly improve the plate shape qualification rate and reduce process debugging time and cost. Attached Figure Description
[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0022] Figure 1 This is a schematic diagram of the original plate shape analyzer dataset provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the region division for characterizing the shape of a thin-gauge high-strength steel quenched plate provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the method flow provided in an embodiment of the present invention. Detailed Implementation
[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0024] In the following description, specific embodiments of the invention will be illustrated with reference to steps and symbols performed by one or more computers, unless otherwise stated. Therefore, these steps and operations will be referred to several times as being performed by a computer, and computer execution as referred to herein includes operations by a computer processing unit representing electronic signals of data in a structured format. This operation transforms the data or maintains it at a location in the computer's memory system, which can be reconfigured or otherwise alter the operation of the computer in a manner well known to those skilled in the art. The data structure maintained by the data is the physical location of the memory, which has specific characteristics defined by the data format. However, the principles of the invention described above are not intended to be limiting, and those skilled in the art will understand that many of the following steps and operations can also be implemented in hardware.
[0025] The terms "module" or "unit" as used herein can be considered as software objects executing on the computing system. Different components, modules, engines, and services described herein can be considered as implementations on the computing system. The apparatus and methods described herein are preferably implemented in software, but can also be implemented in hardware, both of which are within the scope of this invention.
[0026] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.
[0027] In this embodiment of the invention, a method for characterizing and analyzing defects in the quenched shape of thin-gauge high-strength steel is provided. Specifically, it addresses the lack of quantitative characterization methods and clear defect determination methods for the shape characteristics of quenched thin-gauge high-strength steel, which prevents quantitative analysis and optimization of the quenched shape. The invention provides a characterization method and defect analysis and determination method for the shape characteristics of quenched thin-gauge high-strength steel. Figure 3 As shown, it includes the following steps: S1: Acquire steel plate shape detection data online and form a plate shape height dataset; S2: Divide the plate height dataset into regions: head region, middle region, edge region, and tail region. S3: Calculate the plate shape characteristic value at a specific location (head, middle, edge, and tail) of the steel plate; S4: Analyze and determine the plate shape quality and main defect types of the steel plate.
[0028] Furthermore, online acquisition of steel plate shape detection data forms a plate height dataset, including: the shapeline plate shape analyzer at the quenching machine exit scans the height of the entire upper surface of the steel plate after quenching, forming a .csv delimited data file of steel plate surface height detection; firstly, Python is used to parse the CSV file into columns, obtaining an easily readable and calculable .xlsx file. The first line of the file contains the coordinates in the width direction of the steel plate, the first column contains the coordinates in the length direction of the steel plate, and the remaining values represent the height of the corresponding points.
[0029] Furthermore, the plate height dataset is divided into regions: the head region, the middle region, the edge region, and the tail region of the steel plate, including: (1) The head of the steel plate is the area 1m away from the edge of the plate head; (2) The tail of the steel plate is the area 1m away from the edge of the tail of the plate; (3) The steel plate edge is divided into the right side and the left side. The right side is the area 0.2m away from the right edge of the steel plate after removing the head and tail. The left side is the area 0.2m away from the left edge of the steel plate after removing the head and tail. (4) The middle part of the steel plate is the area remaining after removing the head, tail and middle parts.
[0030] Furthermore, the plate shape characteristic values at specific locations (head, middle, edge, and tail) of the steel plate are calculated, including: 1) Height of head and tail curvature Taking head warp height as an example, the calculation method is as follows: Taking the i-th column of head data as an example, take the i-th column of head position data. Each column of data has 100 data points. According to the data characteristics of the aforementioned plate shape instrument xlsx file, the coordinates of each data point are (y... i ,z i By fitting these n data points using the least squares method, the slope m can be calculated. i and intercept b i The calculation formula is as follows:
[0031]
[0032] An intercept value b can be obtained for each column of data in the head region using this method. Assuming there are j columns of detection data in the head, where j is related to the width of the steel plate, and j b values are obtained, the final head warping height h_head is:
[0033] `thickness` refers to the thickness specification of the steel plate. Similarly, the warp height `h_tail` of the tail can be calculated. The calculation method for the tail warp height `h_tail` is exactly the same as that for the head, except that the calculation area is replaced with the tail area.
[0034] 2) C-curvature value in the middle section Calculate the C-curve value from the data in the middle region of the steel plate. For the i-th row of data, take the data points (x1, z1) in the first column, (x2, z2) in the last column, and (x3, z3) in the middle column to calculate a height difference value c. i :c i= z3 - (z1 + z2) / 2).
[0035] For each row of data in the middle region, a height difference c value can be obtained in this way. Finally, j c values are obtained. The final middle C warp amplitude c value is:
[0036] 3) Waviness condition characteristic values The waviness condition characteristic values mainly include five values: the left edge IU, the right edge IU, the left quarter IU, the right quarter IU, and the middle IU.
[0037] Taking the left edge IU as an example to illustrate the calculation method of the IU value: Select a column of data at a position 5 cm away from the left edge in the width direction. Assume there are n points in total, and n is related to the length of the steel plate. Use the Pythagorean theorem to calculate the straight-line distance between adjacent detection data points. The calculation formula for the sum of the distances L of all points is as follows:
[0038] The projection distance between the first data point and the last data point is L0, and L0 is related to the length of the steel plate. The calculation formula for IU is as follows:
[0039] The calculation methods for the IU values at other positions can be obtained similarly: Take the longitudinal data at a position 5 cm away from the right edge in the width direction and calculate the right edge IU_right.
[0040] Take the longitudinal data at a position one-quarter of the width away from the left edge in the width direction and calculate the left quarter IU_1 / 4_left.
[0041] Take the longitudinal data at a position one-quarter of the width away from the right edge in the width direction and calculate the right quarter IU_1 / 4_right.
[0042] Take the longitudinal data at the middle position in the width direction and calculate the middle IU_middle.
[0043] Furthermore, analyze and determine the shape quality and main defect types of the steel plate, including: 1) Determination of head warping defect Head defects are divided into two types: upward warping and downward buckling Assume the head upward warping threshold is h_rg_up (positive value). If h_head > h_rg_up, it is determined that there is an upward warping defect at the head; Assume the head downward buckling threshold is h_rg_down (negative value). If h_head < h_rg_down, it is determined that there is a downward buckling defect at the head; 2)判定 of tail warping defect Tail defects are divided into two types: upward warping and downward buckling Assume the upward warping threshold of the head is t_rg_up (positive value). If h_tail > t_rg_up, it is determined that there is an upward warping defect at the tail; Assume the downward buckling threshold of the head is t_rg_down (negative value). If h_tail < t_rg_down, it is determined that there is a downward buckling defect at the tail; 3)判定 of C - warping defect C - warping defects are divided into two types: upward C - warping and downward C - warping Assume the upward C - warping threshold is c_rgmax (positive value). If c_bend > c_rgmax, it is determined that there is an upward C - warping defect in the middle of the steel plate; Assume the downward C - warping threshold is c_rgmin (negative value). If c_bend < c_rgmin, it is determined that there is a downward C - warping defect in the middle of the steel plate; 4)判定 of waviness defect Assume the IU threshold of the left edge is IU_leftrg. If IU_left > IU_leftrg, it is determined that there is a left - hand edge wave defect; Assume the IU threshold of the right edge is IU_rightrg. If IU_right > IU_rightrg, it is determined that there is a right - hand edge wave defect; Assume the IU threshold of the left 1 / 4 edge is IU_left1 / 4rg. If IU_1 / 4_left > IU_leftrg, it is determined that there is a left - hand 1 / 4 wave defect; Assume the IU threshold of the right 1 / 4 edge is IU_right1 / 4rg. If IU_1 / 4_right > IU_rightrg, it is determined that there is a right - hand 1 / 4 wave defect; Assume the IU threshold in the middle is IU_middlerg. If IU_middle > IU_rightrg, it is determined that there is a middle wave defect; Based on the above analysis results, the comprehensive plate shape of the thin - gauge ultra - high - strength steel quenched plate is finally obtained. Thus, the design of the method for characterizing and analyzing the defects of the thin - gauge ultra - high - strength steel quenched plate shape is completed.
[0044] In another embodiment of the present invention, taking a quenched plate of steel grade NM500, with a thickness of 8 mm, a width of 1400 mm, and a length of 9600 mm produced by a heat treatment plant of a certain iron and steel enterprise as an example, the specific implementation manner of the present invention is introduced.
[0045] Step 1: Obtain the steel plate surface height detection data file generated by the Shapeline plate profiler scanning the entire upper surface of the steel plate; use Python to split and parse the CSV file to obtain an XLSX file that is easy to read and calculate. For example... Figure 1 The image shows the parsed XLSX file. The first line of the file contains the coordinates along the width of the steel plate, the first column contains the coordinates along the length of the steel plate, and the values in the middle represent the height of the plate surface.
[0046] Step 2: Divide the plate height dataset into regions: head region, middle region, edge region, and tail region, such as... Figure 2 As shown: (1) The head of the steel plate is the area 1m away from the edge of the plate head; (2) The tail of the steel plate is the area 1m away from the edge of the tail of the plate; (3) The steel plate edge is divided into the right side and the left side. The right side is the area 0.2m away from the right edge of the steel plate after removing the head and tail. The left side is the area 0.2m away from the left edge of the steel plate after removing the head and tail. (4) The middle part of the steel plate is the area remaining after removing the head, tail and middle parts.
[0047] Step 3: Calculate the plate shape characteristic values for specific locations on the steel plate (head, middle, edge, and tail), including: (1) Head and tail curvature height, the head curvature height is calculated as follows: Each column of data in the header region has 100 data points. Taking the first column of data from the header, the coordinates of each data point are (y...). i ,z i The coordinates of these points are (10,10.12), (20,10.27), (30,10.32), (40,10.39)...(970,7.19), (980,7.23), (990,7.25), (1000,7.27). By performing a line fitting using the least squares method on these 100 data points, the slope m1 and intercept b1 of the fitted data in the first column can be calculated. The calculation formula is as follows:
[0048] 9.88 For each column of data in the head region, an intercept value b can be obtained using this method, resulting in 153 b values. The final head warp height can then be calculated. for:
[0049] Similarly, the warp height of the tail, h_tail, can be calculated as -2.39, and the tail drooping amplitude as -2.39mm.
[0050] (2) C-curvature value in the middle Calculate the C-curve value by taking data from the middle region of the steel plate. For the 100th row of data, take the data point (10, 7.27) in the first column, the data point (1530, 6.76) in the last column, and a data point (770, 9.11) in the middle column. A height difference value c can be calculated. 100
[0051] For each row of data in the central region, a height difference value c can be obtained using this method. The corresponding row number range is [100, 864], totaling 764 values. The final C-curve value c for the central region is:
[0052] (3) Wave shape characteristic value The characteristic values of the wave pattern mainly include five values: IU of the left side, IU of the right side, IU of the left quarter, IU of the right quarter, and IU of the middle.
[0053] Taking the left side IU as an example, the calculation method of IU value is explained: Select a column of data located 5cm away from the left side in the width direction, totaling 764 points. The coordinates of these points are (1010, 7.40), (1020, 7.42), (1030, 7.43), (1040, 7.47)...(8630, 8.09), (8640, 8.11). Using the Pythagorean theorem to calculate the straight-line distance between adjacent data points, the formula for calculating the sum of distances L of all points is as follows:
[0054] The distance between the first and last data points is L0, where L0 = 7630 mm. The formula for calculating the length difference IU is as follows:
[0055] The calculation method for IU values at other locations is similar: Taking the vertical data at a position 5cm away from the right edge in the width direction, the IU_right value for the right edge is calculated to be 0.8; Taking the vertical data at a position one-quarter the width away from the left edge in the width direction, the left quarter IU_1 / 4_left = 0.75 is calculated; Take the longitudinal data at a position one-fourth of the width from the right edge in the width direction, and calculate to obtain the right one-fourth IU_1 / 4_right = 1.06; Take the longitudinal data at the middle position in the width direction, and calculate to obtain the middle IU_middle = 0.95.
[0056] Step 4: Analyze and determine the shape quality and main defect types of the steel plate, including: (1) Judgment of head warping defect The head defects are divided into two types: upward warping and downward buckling. The upward warping threshold of the head is h_rg_up = 3 mm, and the downward buckling threshold is h_rg_down = -3 mm. If h_head > h_rg_up and h_tail > t_rg_down, it is determined that there is an upward warping defect at the head; (2) Judgment of tail warping defect The tail defects are divided into two types: upward warping and downward buckling. The upward warping threshold of the tail is t_rg_up = 3 mm, and the downward buckling threshold of the tail is t_rg_down = -3 mm. h_tail = -2.39, h_tail < t_rg_up, and h_tail > t_rg_down, then it is determined that the tail is downward buckled, but it meets the requirements and there is no defect; (3) Judgment of C-warping defect The C-warping defect is divided into two types: upper C-warping and lower C-warping. The upper C-warping threshold is 2 (positive value), and the lower C-warping threshold is -2. C bend = 0.9, c_bend < c_rgmax, and c_bend > c_rgmin, then it is determined that there is no C-warping defect in the middle of the steel plate; (4) Judgment of waviness defect The IU threshold of the left edge is 10. If IU_left > IU_leftrg, it is determined that there is no left edge wave defect; The IU threshold of the right edge is 10. If IU_right > IU_rightrg, it is determined that there is no right edge wave defect; The IU threshold of the right one-fourth is 10. If IU_1 / 4_right > IU_rightrg, it is determined that there is no right one-fourth wave defect; The IU threshold of the left one-fourth is 10. If IU_1 / 4_left > IU_leftrg, it is determined that there is no left one-fourth wave defect; The IU threshold of the middle is 10. If IU_middle > IU_middlerg, it is determined that there is no middle wave defect.
[0057] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.
[0058] Therefore, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, the computer program being loaded by a processor to execute the steps of any method provided in the embodiments of the present invention.
[0059] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.
[0060] The computer-readable storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.
[0061] Since the computer program stored in the computer-readable storage medium can execute the steps in any of the methods provided in the embodiments of the present invention, the beneficial effects that any of the methods provided in the embodiments of the present invention can achieve can be realized, as detailed in the preceding embodiments, and will not be repeated here.
[0062] The foregoing has provided a detailed description of the method and medium for characterizing the shape and analyzing and judging defects of thin-gauge high-strength steel quenched plates according to embodiments of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.
Claims
1. A method for characterizing the shape and analyzing and judging defects in thin-gauge high-strength steel quenched plates, characterized in that, include: The surface three-dimensional contour data of the steel plate after quenching is acquired online to form a plate height dataset containing the length direction coordinates, width direction coordinates and corresponding height values of the steel plate. The plate height dataset is divided into regions according to the length and width of the steel plate, at least into a head region, a tail region, a left side region, a right side region, and a middle region; Calculate the head warp height of the head region, the tail warp height of the tail region, the C-warp amplitude value of the middle region, and the wave-shaped characteristic values of the left side region, the right side region, and the middle region, respectively. The calculated feature values are compared with the preset corresponding defect judgment thresholds to determine the plate shape quality and main defect types of the steel plate.
2. The method according to claim 1, characterized in that, The plate shape and height dataset is derived from the plate shape gauge scanning data at the outlet of the quenching machine. This data is stored in a three-dimensional data format that includes length direction coordinates, width direction coordinates, and height values.
3. The method according to claim 1, characterized in that, The process of dividing the plate height dataset into regions along the length and width of the steel plate includes at least a head region, a tail region, a left side region, a right side region, and a middle region. Head region: The region extending inward along the length direction from the edge of the steel plate head within a first preset distance; Tail region: The region extending inward along the length direction from the tail edge of the steel plate within a second preset distance; Left side region: Within the remaining length after removing the head and tail regions, the region extends inward along the width direction from the left edge of the steel plate at a third preset distance; Right side region: Within the remaining length after removing the head and tail regions, the region extends inward along the width direction from the right edge of the steel plate at a fourth preset distance; Central region: The region remaining after removing the head region, tail region, left side region, and right side region.
4. The method according to claim 3, characterized in that, The calculation methods for the head warp height and tail warp height are as follows: For each column of data in the head or tail region, the column contains multiple data points distributed along the length of the steel plate. The coordinates of each data point are (yi, zi), where yi is the length direction coordinate and zi is the height value. The least squares method is used to fit a straight line to all data points in the column to obtain the intercept bi of the fitted line. The average of the intercepts bi calculated for all columns in the region is denoted as average(bi). Then the warping height h in this region is equal to average(bi) - thickness, where thickness is the correction value for the steel plate thickness specification. When h is positive, it indicates an upward curve; when h is negative, it indicates a downward curve.
5. The method according to claim 4, characterized in that, The calculation method for the C-curvature value is as follows: For each row of data in the middle region, the row of data corresponds to a fixed position along the length of the steel plate. Take the left, right and middle data points of the row, and record their height values as zleft, zright and zmid respectively. Calculate the C-curve value ci = zmid - (zleft + zright) / 2 for the row. The average value of Cbend is calculated as average(ci) for all rows in the central region. When Cbend is positive, it indicates a downward C-curve; when Cbend is negative, it indicates an upward C-curve.
6. The method according to claim 5, characterized in that, The method for calculating the wave shape characteristic value is as follows: Select a column of data along the length of the steel plate at the location to be calculated. This column of data contains multiple data points distributed along the length. The distance between adjacent data points is calculated as a straight line distance using the Pythagorean theorem. The actual curve length L is obtained by summing the straight line distances between all adjacent data points. Calculate the projected straight-line distance L0 between the first and last data points in this column of data; The wave-shaped characteristic value at that location is IU = (L - L0) / L0 × 10 5 ; The wave-shaped feature values include: IU at the left side, IU at the right side, IU at the left quarter width, IU at the right quarter width, and IU at the center.
7. The method according to claim 6, characterized in that, The defect judgment threshold is preset based on at least one of the following factors: steel type, thickness specification, width specification, and user plate shape acceptance standard.
8. The method according to claim 7, characterized in that, The step of comparing the calculated feature values with preset corresponding defect judgment thresholds to determine the plate shape quality and main defect types of the steel plate includes: If the head curvature height is greater than the head upturn threshold, it is determined that there is a head upturn defect; if the head curvature height is less than the head downturn threshold, it is determined that there is a head downturn defect. If the height of the tail warp is greater than the tail warp threshold, it is determined that there is a tail warp defect; if the height of the tail warp is less than the tail droop threshold, it is determined that there is a tail droop defect. If the C-curve amplitude value is greater than the upper C-curve threshold, it is determined that there is an upper C-curve defect; if the C-curve amplitude value is less than the lower C-curve threshold, it is determined that there is a lower C-curve defect. If the IU of the left side is greater than the left side wave threshold, then a left side wave defect is determined to exist; if the IU of the right side is greater than the right side wave threshold, then a right side wave defect is determined to exist; if the IU of the middle part is greater than the middle wave threshold, then a middle wave defect is determined to exist.
9. The method according to claim 3, characterized in that, The first preset distance is 1m, the second preset distance is 1m, the third preset distance is 0.2m, and the fourth preset distance is 0.2m.
10. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 9.