Method for detecting defects in the subsurface of steel

Abstract

The application provides a steel material subsurface defect detection method. The method comprises: dividing the steel material to be detected into two parts according to the rolling direction, and marking the divided steel material to be detected, wherein the defect positions of the divided steel material to be detected have a correlation relationship, and the mark of each steel material to be detected represents the position state of the steel material to be detected before being divided; dividing the sample divided into two parts into an oxidation sample and an analysis sample, oxidizing the oxidation sample, determining the defect position of the oxidation sample, and marking the defect position as A defect position; determining the B defect position of the analysis sample according to the position relationship of the marks of the oxidation sample and the analysis sample and the A defect position; and performing subsurface defect detection on the B defect position to obtain the subsurface defect detection result of the steel material to be detected.

Description

Technical Field

[0001] This application relates to the field of metal processing technology, and in particular to a method for detecting subsurface defects in steel. Background Technology

[0002] Cold-rolled strip steel is an important raw material for various processing and manufacturing industries. With the continuous development of industry, the quality requirements for cold-rolled strip steel are becoming increasingly stringent. Due to factors such as the long production process and thin dimensions of cold-rolled strip steel, as well as reasons related to raw materials, rolling equipment, processing technology, and system control, various defects are prone to appear on the surface. The most common defects include linear or strip-shaped defects, inclusions, voids, and iron oxide scale indentation. Linear defects are one of the most common defects in cold-rolled thin plates. These defects usually extend along the rolling direction and appear as lines or strips.

[0003] Because the process from steelmaking to finished product is lengthy, many factors can lead to linear defects in cold-rolled sheets. Therefore, the causes of linear defects require specific analysis on a case-by-case basis to determine the root cause and subsequently improve the production line to resolve the issue. However, some linear inclusion defects exist on the subsurface after cold rolling, making them difficult to locate for detailed inspection. This can easily damage the defect's condition during inspection, leading to the loss of accurate defect information and making it difficult to determine the cause, resulting in low reliability of defect detection. Summary of the Invention

[0004] This application provides a method for detecting subsurface defects in steel, which can avoid damaging the defects during the detection process and thus obtain more reliable detection results.

[0005] In a first aspect, this application provides a method for detecting subsurface defects in steel, the method comprising:

[0006] The steel to be tested is divided into two parts according to the rolling direction, and the divided samples are marked. The defect locations of the divided samples are related, and the mark of each sample indicates the position of the sample before division.

[0007] The sample to be tested is divided into two parts: the sample to be oxidized and the sample to be analyzed.

[0008] The sample to be oxidized is subjected to oxidation treatment to determine the defect location of the sample to be oxidized, which is denoted as defect location A.

[0009] Based on the positional relationship between the markings on the sample to be oxidized and the sample to be analyzed, and the location of defect A, determine the location of defect B in the sample to be analyzed.

[0010] Subsurface defect detection is performed on the location of defect B to obtain the subsurface defect detection results of the steel to be tested.

[0011] In some possible implementations, determining the location of defect B in the sample to be analyzed based on the positional relationship between the markers on the sample to be oxidized and the sample to be analyzed, and the location of defect A, includes:

[0012] According to the markings, the sample to be oxidized and the sample to be analyzed are correlated based on their positional state before segmentation;

[0013] Based on the location of defect A and its position before segmentation, the corresponding position of the sample to be analyzed is determined as the location of defect B.

[0014] In some possible implementations, the step of mapping the sample to be oxidized to the sample to be analyzed based on the pre-segmentation positional state according to the marking includes:

[0015] According to the markings, the sample to be oxidized and the sample to be analyzed are spliced ​​together;

[0016] Based on the positional relationship between the assembled sample to be oxidized and the sample to be analyzed, the sample to be oxidized will be matched with the adjacent sample to be analyzed.

[0017] In some possible implementations, the A defect location is a linear defect related to the rolling direction, and determining the corresponding position of the sample to be analyzed as the B defect location based on the A defect location and the positional state before segmentation includes:

[0018] Based on the location of defect A, and according to the positional state before segmentation, draw an extension line to the sample to be analyzed to the location of defect A;

[0019] The position of the extension line on the sample to be analyzed is determined as the location of defect B.

[0020] In some possible implementations, the step of dividing the steel to be tested into two parts according to the rolling direction and marking the divided samples includes:

[0021] The sample to be tested is divided into multiple parts perpendicular to the rolling direction;

[0022] The segmented samples to be tested are labeled.

[0023] In some possible implementations, the oxidation treatment of the sample to be oxidized, and the determination of the defect location of the sample to be oxidized, denoted as defect location A, includes:

[0024] When the temperature inside the muffle furnace reaches the preset temperature, the sample to be oxidized is placed into the muffle furnace;

[0025] While controlling the temperature inside the muffle furnace within a preset temperature range, the sample to be oxidized is heated for a preset time to oxidize the sample.

[0026] Based on the surface condition of the sample to be oxidized after oxidation, the defect location of the sample to be oxidized is determined and denoted as defect location A.

[0027] In some possible implementations, after heating the sample to be oxidized for a preset time to oxidize the sample while controlling the temperature inside the muffle furnace within a preset temperature range, the method further includes:

[0028] The sample to be oxidized was cooled to room temperature to stop the oxidation reaction.

[0029] In some possible implementations, the preset temperature range is 500°C to 700°C, and the preset duration is 3 minutes to 10 minutes.

[0030] In some possible implementations, the subsurface defect detection at the location of defect B to obtain the subsurface defect detection result of the steel to be inspected includes:

[0031] A metallographic sample is inlaid at the location of defect B, followed by grinding to remove the surface coating or metal substrate at the location of defect B, and then polishing is performed.

[0032] Subsurface defect information was obtained by detecting the location of the B defect after polishing using a microscope.

[0033] Based on the subsurface defect information, the subsurface defect detection result is determined.

[0034] In some possible implementations, the subsurface defect detection at the B defect location after polishing using a microscope to obtain subsurface defect information includes:

[0035] The B defect location was analyzed for composition and morphology using an electron microscope.

[0036] Based on the compositional analysis results at the location of defect B, determine the composition of the components at the location of defect B;

[0037] The step of determining the subsurface defect detection result based on the subsurface defect information includes:

[0038] Based on the composition of the components at the location of defect B, the defect type and cause are determined.

[0039] The steel subsurface defect detection method, apparatus, equipment, storage medium, and product provided in this application involve cutting and segmenting a sample from the steel to be tested, dividing it into an oxidized sample and an analytical sample, and marking each segmented sample. This ensures that the oxidized and unoxidized portions of the sample correspond to each other after subsequent oxidation, restoring them to their original positions before segmentation. Oxidizing the sample exposes its defects, and observing these defects helps determine their corresponding positions on the analytical sample. Even if defects are not visible in the unoxidized state, they can be located using the markings on the oxidized sample. Subsequently, potential defect locations on the unoxidized sample are detected, and the defects in the sample to be oxidized are revealed through prior oxidation. By identifying the defect locations on the oxidized sample and using precise marking and sampling, damage to the analytical sample's defects is avoided during the testing process, ensuring that the original defect information is not destroyed during analysis, thus obtaining more accurate detection results. Attached Figure Description

[0040] This application can be better understood from the following description of specific embodiments in conjunction with the accompanying drawings, wherein:

[0041] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings, wherein the same or similar reference numerals denote the same or similar features.

[0042] Figure 1 This is a flowchart of a method for detecting subsurface defects in steel according to an embodiment of this application;

[0043] Figure 2 This is a schematic diagram of the segmentation markings on the steel to be inspected provided in an embodiment of this application;

[0044] Figure 3 This is a schematic diagram of defects in a sample to be tested provided in one embodiment of this application;

[0045] Figure 4 This is a schematic diagram illustrating the determination of defect location B according to an embodiment of this application;

[0046] Figure 5 These are example images of optical microscopes provided in embodiments of this application;

[0047] Figure 6 These are example scanning electron microscope images provided in embodiments of this application. Detailed Implementation

[0048] The features and exemplary embodiments of this application will now be described in detail. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are intended only to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0049] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0050] Cold-rolled strip steel is a primary raw material for numerous industries, including automobile manufacturing, home appliance manufacturing, container production, and enamelware manufacturing. With continuous industrial development, the quality requirements for cold-rolled strip steel are becoming increasingly stringent, and surface defects are a significant factor affecting product quality. However, due to the long production process, thin dimensions, and factors related to raw materials, rolling equipment, processing technology, and system control, cold-rolled strip steel is prone to various surface defects. Common defects include linear or strip-shaped defects, inclusions, voids, and indented iron oxide scale. However, some defects, primarily linear inclusions, exist on the subsurface after cold rolling and are not detected by surface inspection instruments. These defects only become apparent after galvanizing or enamel coating. Furthermore, these linear inclusion defects, occurring on the subsurface and only detectable after galvanizing or enamel coating, are often difficult to detect during sampling and testing. This is partly due to the difficulty in selecting sampling locations and partly because the surface coating can easily damage the defect during inspection, leading to the loss of accurate defect information.

[0051] The inventors, in their research addressing the aforementioned problems, discovered that one specific reason for these issues is the difficulty in locating defects and selecting sampling positions. If the sampling position could be accurately determined, the removal of the coating from the defective area could be performed with greater precision, avoiding damage to the defect. Therefore, if the location of subsurface defects can be accurately determined, the original information about the defect can be preserved, leading to more accurate defect analysis.

[0052] To address the problems of existing technologies, this application provides a method for detecting subsurface defects in steel. The method for detecting subsurface defects in steel provided by this application is described below.

[0053] Figure 1 A schematic flowchart of a method for detecting subsurface defects in steel according to an embodiment of this application is shown. Figure 1 As shown, the method includes the following steps S101 to S103.

[0054] Step S101: Divide the steel to be tested into two parts according to the rolling direction, and mark the divided samples. The defect positions of the divided samples are related, and the above mark of each sample indicates the position of the divided sample before the division.

[0055] In practice, firstly, the rolling direction of the steel to be tested is determined. Then, according to the rolling direction, the steel is divided into sections of a certain length. Each section is marked for subsequent testing and data analysis. These marks can be numbers, letters, or other symbols, and the position of the steel before division can be reconstructed based on the marks.

[0056] The defects in the sample to be tested can be linear or blocky. Based on a segmented sample, the location of defects on other samples can be inferred.

[0057] For example, you can refer to Figure 2 ,like Figure 2 As shown, the steel to be tested is divided into two pieces. The upper sample 201 is marked with the letter "A", and the lower sample 202 is marked with the letter "B". In this way, even if the positions of the two samples are scrambled during subsequent processing, they can be restored to their original positions according to the letter markings.

[0058] As another example, the cut sample needs to be marked with its upper and lower surfaces, rolling direction, and operating side, and also marked with restoration marks. After cutting, the sample should be reassembled and photographed for record-keeping. In addition, the markings on the sample to be oxidized should ensure that they are identifiable after oxidation.

[0059] Step S102: Divide the above-segmented sample into a sample to be oxidized and a sample to be analyzed.

[0060] The sample to be oxidized can refer to a sample that has been selected to undergo surface oxidation treatment to expose defects.

[0061] The sample to be analyzed can be a sample used to assess the quality of the original material.

[0062] In practice, samples requiring oxidation are randomly selected. Then, all other samples are categorized as samples to be analyzed, or samples requiring detailed analysis are selected from the unoxidized samples. For example, sample 201 can be designated as the sample to be oxidized, and sample 202 as the sample to be analyzed.

[0063] Step S103: Perform oxidation treatment on the above sample to be oxidized, determine the defect location of the above sample to be oxidized, and record it as defect location A.

[0064] In practice, the sample to be oxidized is placed in a suitable oxidation treatment device, typically a heating furnace or oxidation chamber. The sample surface is exposed to the oxidation environment, meaning it comes into contact with oxygen, water vapor, or other oxidizing agents. The specific oxidation treatment time depends on the desired degree of oxidation and the surface characteristics of the sample. After oxidation, an oxide layer forms on the sample surface, typically exhibiting different colors or textures. After the oxidation treatment is complete, the sample is removed and its surface oxidation is observed. By observing the oxidized sample surface, the locations of potential A-type defects can be identified. These defects can be surface defects beneath the oxide layer, such as bubbles or inclusions.

[0065] For example, you can refer to Figure 3 ,like Figure 3 As shown, after oxidation, the sample 201 to be tested showed defective parts 2011 and 2031. The location of this defect is the A defect location.

[0066] In some embodiments, in order to rapidly oxidize the sample to be oxidized, the above-mentioned S103 may include steps A1 to C1:

[0067] Step A1: When the temperature inside the muffle furnace reaches the preset temperature, place the sample to be oxidized into the muffle furnace.

[0068] In practice, a sample requiring surface oxidation treatment is selected from the steel to be tested, ensuring its surface is clean and free of oil or other contaminants. The heating parameters of the muffle furnace, such as heating power, heating time, and heating rate, are adjusted according to the sample's size, material, and oxidation requirements. After the muffle furnace reaches the preset temperature, the sample is placed into the furnace chamber. To avoid interference or contact between samples, a suitable sample holder or support can be used to place the samples inside the furnace chamber.

[0069] Step B1: While controlling the temperature inside the muffle furnace within the preset temperature range, heat the sample to be oxidized for a preset time to oxidize the sample.

[0070] In practice, once the temperature inside the muffle furnace approaches the preset temperature range, the temperature change is continuously monitored, and the heating power is adjusted as needed to ensure that the temperature remains stable within the required range. Once the temperature inside the muffle furnace stabilizes within the preset temperature range, a timer is started to ensure that the sample to be oxidized is sufficiently heated within the preset time.

[0071] Step C1: Based on the surface condition of the sample to be oxidized, determine the defect location of the sample to be oxidized, and record it as defect location A.

[0072] In practice, the surface image of the sample to be oxidized can be digitized, and image analysis software can be used for defect analysis. By calculating and comparing features such as texture, color changes, and unevenness of the sample surface, potential defect locations can be identified.

[0073] As another example, surface defect detection equipment, such as infrared scanners, ultrasonic testing equipment, or magnetic particle testing devices, can be used to perform a comprehensive scan of the sample to be oxidized. This allows for the detection of defects such as cracks, pores, and inclusions on the sample surface.

[0074] The above-described method in this application embodiment involves placing the sample to be oxidized into the muffle furnace when the temperature inside the furnace reaches a preset temperature, and then heating the sample in the muffle furnace for a preset time to oxidize it. Based on the surface condition of the oxidized sample, the defect location can be determined and denoted as defect location A. Using a muffle furnace for heating allows for rapid oxidation of the sample.

[0075] In some embodiments, to reduce the impact of the cooling process on the sample to be oxidized, the method further includes, after B1, the following:

[0076] The sample to be oxidized was cooled to room temperature to stop the oxidation reaction.

[0077] In practice, the heating system of the muffle furnace is stopped. After the temperature inside the muffle furnace gradually drops to a safe range, the furnace door is opened to allow room temperature air to enter the furnace chamber and expose the sample to be oxidized to the external environment. The sample is then placed inside the muffle furnace and allowed to cool naturally to room temperature.

[0078] The above-described method in this application embodiment reduces the impact of the cooling process on the sample to be oxidized by air-cooling it to room temperature after heating in a muffle furnace.

[0079] In some embodiments, in order to oxidize the sample to a suitable degree, the preset temperature range is 500°C to 700°C, and the preset time is 3 minutes to 10 minutes.

[0080] Step S104: Determine the position of defect B in the sample to be analyzed based on the positional relationship between the markings on the sample to be oxidized and the sample to be analyzed, as well as the position of defect A.

[0081] In practice, the sample to be analyzed is compared with the sample to be oxidized according to the markings. Based on the markings on the sample to be oxidized and the location of defect A, a corresponding reference point is determined on the sample to be analyzed. Thus, based on the defect location on the sample to be oxidized, denoted as defect A, the location of possible defect B is determined on the sample to be analyzed.

[0082] In some implementations, in order to accurately determine the location of defect B, the above-mentioned S104 may include steps A2 to B2:

[0083] Step A2: According to the above markings, match the above sample to be oxidized with the above sample to be analyzed based on their positional state before segmentation.

[0084] In practice, based on previous markings and records, the segmented sample to be oxidized is matched with the sample to be analyzed to confirm whether the positional state between the sample to be oxidized and the sample to be analyzed is correct.

[0085] Step B2: Based on the above A defect location and the positional state before segmentation, the corresponding position of the sample to be analyzed is determined as the B defect location.

[0086] In practice, based on the marking of defect A's location and its positional state before segmentation, the location of potential defect B on the sample to be analyzed is determined. Since subsurface defects may be truncated during steel segmentation, a defect at the edge of the sample to be oxidized may be part of a larger defect, with the other part of that defect located at the corresponding position on the sample to be analyzed. For details, please refer to... Figure 4 For defective parts 2011 and 2031, possible defective parts 2021 and 2041 can be identified, and their locations are the locations of defect B.

[0087] In the embodiments of this application, the above-described method, according to the previous markings, corresponds the sample to be oxidized with the sample to be analyzed based on the positional state before segmentation. Then, based on the positional state before segmentation, according to the defect position A, the corresponding position on the sample to be analyzed is determined as the defect position B. This allows for accurate determination of the defect position B.

[0088] In some embodiments, in order to accurately correspond the sample to be oxidized with the sample to be analyzed, the above-mentioned A2 includes steps A3 to B3:

[0089] Step A3: According to the above markings, splice the above sample to be oxidized with the above sample to be analyzed.

[0090] In practice, based on the previous markings, the marking positions of the sample to be oxidized and the sample to be analyzed are aligned, and then the sample to be oxidized and the sample to be analyzed are spliced ​​together.

[0091] Step B3: Based on the positional relationship between the spliced ​​sample to be oxidized and the sample to be analyzed, match the sample to be oxidized with the adjacent sample to be analyzed.

[0092] In practice, the correspondence between the sample to be oxidized and the adjacent sample to be analyzed is determined based on the actual positional relationship between the spliced ​​sample to be oxidized and the sample to be analyzed.

[0093] The above-described method in this application embodiment splices the sample to be oxidized and the sample to be analyzed back to their pre-splitting state according to markings, and then determines the correspondence between the sample to be oxidized and the adjacent sample to be analyzed based on the positional relationship between the spliced ​​sample to be oxidized and the sample to be analyzed. This enables accurate correspondence between the sample to be oxidized and the sample to be analyzed.

[0094] In some embodiments, in order to accurately determine the location of defect B, when the location of defect A is a linear defect related to the rolling direction, the aforementioned defect B2 includes steps A4 to B4:

[0095] Step A4: Based on the above-mentioned defect A location, and according to the positional state before segmentation, draw an extension line to the above-mentioned sample to be analyzed at the above-mentioned defect A location.

[0096] In practice, linear defects are generally formed during the rolling process and are in the same direction as the rolling. After determining the location of defect A, an extension line related to the defect is drawn on the sample to be analyzed, following the direction of defect A.

[0097] Step B4: Determine the location of defect B on the sample to be analyzed by the position of the extended line.

[0098] In the embodiments of this application, when defect A is a linear defect related to the rolling direction, the location of defect B is determined by extending a line from defect A to the sample to be analyzed according to the position state before segmentation, and then determining the position of the extended line on the sample to be analyzed as defect B. By using the extension line of the linear defect, the location of defect B can be accurately determined.

[0099] In some implementations, in order to detect linear defects in the steel to be tested with the highest probability, the above-mentioned S101 includes steps A5 to B5:

[0100] Step A5: Divide the steel to be tested into two parts perpendicular to the rolling direction.

[0101] In practice, if the defect to be detected is a linear defect in the steel, that is, a long strip defect in the same direction as the rolling process, the positions to be segmented can be marked on the steel to be inspected perpendicular to the rolling direction. Then, the steel to be inspected is segmented according to the marked positions.

[0102] Step B5: Mark the segmented sample to be tested.

[0103] In the above-described method of this application embodiment, when the A-type defect to be detected is a linear defect related to the rolling direction, the steel to be tested is segmented perpendicular to the rolling direction during segmentation to maximize the segmentation of possible linear defects in the steel to be tested. The segmented samples are then marked. This method can detect linear defects in the steel to be tested with the highest probability.

[0104] Step S105: Perform subsurface defect detection on the above-mentioned defect B location to obtain the subsurface defect detection results of the above-mentioned steel to be tested.

[0105] In practical implementation, appropriate equipment for subsurface defect detection is prepared. The equipment is then used to perform subsurface defect detection. The area surrounding defect B is scanned or inspected at specific points to detect potential subsurface defects such as porosity, inclusions, and cracks. The obtained data is analyzed and processed to identify and assess the type, location, size, and severity of the subsurface defects. Based on the detection results, necessary classification and labeling are performed for subsequent processing and analysis.

[0106] As another example, when necessary, surface preparation work can be carried out around the location of defect B, such as cleaning the surface, removing dirt and coatings, adjusting surface roughness, etc.

[0107] In some embodiments, in order to accurately determine the subsurface defect detection results, the above-mentioned S105 includes steps A6 to C6:

[0108] Step A6: Inlay a metallographic sample at the above-mentioned defect B location, then grind it to remove the surface coating or metal substrate at the above-mentioned defect B location, and then perform polishing treatment.

[0109] In practice, using selected grinding equipment and materials, a metallographic sample is inlaid at the location of defect B, followed by grinding to ensure a smooth and uniform surface. The surface coating is then gradually removed until the underlying subsurface is exposed. The grinding effect is checked regularly to ensure that the coating has been completely removed.

[0110] Step B6: Use a microscope to detect the subsurface defects at the B defect locations after polishing to obtain subsurface defect information.

[0111] In practice, depending on the type and size of the defect to be detected, a suitable microscope is selected, such as an optical microscope or a microscopic X-ray imaging system. The location of the B defect after polishing is observed through the microscope, and the image of the subsurface defect is recorded to obtain subsurface defect information.

[0112] For example, an optical microscope can be used to observe and obtain optical images of the defects, such as... Figure 5 As shown.

[0113] Step C6: Based on the above subsurface defect information, determine the subsurface defect detection result.

[0114] In practice, defects are classified and evaluated based on information about subsurface defects observed under a microscope. The identified subsurface defect detection results are then recorded to obtain the subsurface defect detection results.

[0115] The method described in this application embodiment involves embedding a metallographic sample at the location of defect B, followed by grinding to remove the surface coating or metal substrate at the defect location, and then polishing. This allows for the use of a microscope to detect subsurface defects at the polished defect location, obtaining subsurface defect information. Based on this subsurface defect information, the subsurface defect detection result is then determined. By performing subsurface defect detection at the defect location after grinding using a microscope to obtain subsurface defect information, the subsurface defect detection result can be accurately determined.

[0116] In some implementations, in order to accurately determine the defect type and defect cause, step B6 above includes steps A7 to B7:

[0117] Step A7: Perform compositional and morphological analysis on the above-mentioned defect B location using an electron microscope.

[0118] In practice, the compositional analysis results and morphology of the B defect location are collected by using an electron microscope combined with a component analysis result analyzer.

[0119] Step B7: Based on the compositional analysis results of the above defect location B, determine the compositional composition and defect type of the above defect location B.

[0120] In the specific implementation, the collected component analysis data is processed to identify the peak values ​​of elements and measure their relative intensities. For each identified peak, its area or peak intensity is measured. The peak area is proportional to the amount of the corresponding element, and therefore can be used to estimate the element's content in the sample. The peak areas of each element at the B defect location are converted into their corresponding contents. This allows the determination of the component composition, i.e., the ratio of the contents of each element.

[0121] For example, such as Figure 6 As shown, Figure 6 The image shows the electronic image of the B defect location after component analysis by scanning electron microscopy. The specific elemental content can be obtained from the spectrum, as shown in Table 1.

[0122] Table 1

[0123] Spectrum Figure 1 0.01 19.12 18.70 1.46 60.71 100.00 Spectrum Figure 2 0.02 44.40 41.24 0.00 14.35 100.00 Spectrum Figure 3 0.03 50.85 46.04 0.65 2.43 100.00 Spectrum Figure 4 0.02 50.20 47.07 0.94 1.77 100.00

[0124] Based on the aforementioned subsurface defect information, the subsurface defect detection results are determined, including:

[0125] Based on the composition of the components at the location of defect B, the defect type and cause are determined.

[0126] In practice, based on the analyzed elemental composition and the rolling process, possible defect types are inferred. For example, if a high alumina content is found at defect location B, it may indicate surface defects such as alumina inclusions; if abnormal carbon content is observed, it may involve internal defects such as carbides or carbon segregation. Combining the inference of defect types, possible causes of defects are analyzed. This requires considering factors such as the chemical composition of the material, process parameters, and operating conditions to further infer the reasons for defect formation. For example, a high alumina content may be due to incomplete alumina removal during smelting, causing it to float to the surface or subsurface during slab solidification, or inadequate protective casting leading to aluminum oxidation in the steel; abnormal carbon content may be due to improper process parameters or errors in rolling temperature control.

[0127] The above-described method in this application embodiment uses scanning electron microscopy to perform component and morphological analysis on the B defect location. The component analysis results determine the composition of the B defect location, and then, based on this composition, the defect type and cause can be determined. By utilizing the component analysis results, the defect type and cause can be accurately determined.

[0128] In this embodiment, a sample to be tested is cut from the target steel and divided into two parts: a sample to be oxidized and a sample to be analyzed. Each segmented sample is marked. This ensures that the oxidized and unoxidized portions of the sample correspond to each other after subsequent oxidation, restoring them to their original positions before segmentation. Oxidizing the sample exposes its defects. By observing the defects in the oxidized sample, the corresponding positions on the sample to be analyzed are determined. Even if defects are not visible in the unoxidized state, they can be located using the markings on the oxidized sample. Then, potential defect locations on the unoxidized sample are detected, and the defects in the sample to be oxidized are revealed through prior oxidation. By using the defect locations in the sample to be oxidized, along with precise marking and sampling, damage to the defects in the sample to be analyzed is avoided during the testing process, ensuring that the original defect information is not destroyed during analysis.

[0129] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0130] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0131] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for detecting subsurface defects in steel, characterized in that, include: The steel to be tested is divided into two parts according to the rolling direction, and the divided samples are marked. The defect locations of the divided samples are related, and the mark of each sample indicates the position of the sample before division. The sample to be tested is divided into two parts: the sample to be oxidized and the sample to be analyzed. The sample to be oxidized is subjected to oxidation treatment to determine the defect location of the sample to be oxidized, which is denoted as defect location A. Based on the positional relationship between the markings on the sample to be oxidized and the sample to be analyzed, and the location of defect A, determine the location of defect B in the sample to be analyzed. Subsurface defect detection is performed on the B defect location to obtain the subsurface defect detection result of the steel to be tested; The step of determining the location of defect B in the sample to be analyzed based on the positional relationship between the markings on the sample to be oxidized and the sample to be analyzed, and the location of defect A, includes: According to the markings, the sample to be oxidized and the sample to be analyzed are correlated based on their positional state before segmentation; Based on the location of defect A and its position before segmentation, the corresponding position of the sample to be analyzed is determined as the location of defect B. The step of mapping the sample to be oxidized to the sample to be analyzed based on their positional state before segmentation, according to the marking, includes: According to the markings, the sample to be oxidized and the sample to be analyzed are spliced ​​together; Based on the positional relationship between the spliced ​​sample to be oxidized and the sample to be analyzed, the sample to be oxidized will be matched with the adjacent sample to be analyzed. The A defect location is a linear defect related to the rolling direction. The step of determining the corresponding position of the sample to be analyzed as the B defect location based on the A defect location and the positional state before segmentation includes: Based on the location of defect A, and according to the positional state before segmentation, draw an extension line to the sample to be analyzed to the location of defect A; The position of the extension line on the sample to be analyzed is determined as the location of defect B.

2. The method for detecting subsurface defects in steel according to claim 1, characterized in that, The process of dividing the steel to be tested into two parts according to the rolling direction and marking the divided samples includes: The steel to be tested is divided into two parts perpendicular to the rolling direction; The segmented samples to be tested are labeled.

3. The method for detecting subsurface defects in steel according to claim 1, characterized in that, The oxidation treatment of the sample to be oxidized, and the determination of the defect location of the sample to be oxidized, denoted as defect location A, includes: When the temperature inside the muffle furnace reaches the preset temperature, the sample to be oxidized is placed into the muffle furnace; While controlling the temperature inside the muffle furnace within a preset temperature range, the sample to be oxidized is heated for a preset time to oxidize the sample. Based on the surface condition of the sample to be oxidized after oxidation, the defect location of the sample to be oxidized is determined and denoted as defect location A.

4. The method for detecting subsurface defects in steel according to claim 3, characterized in that, After heating the sample to be oxidized for a preset time to oxidize the sample while controlling the temperature inside the muffle furnace within a preset temperature range, the method further includes: The sample to be oxidized was cooled to room temperature to stop the oxidation reaction.

5. The method for detecting subsurface defects in steel according to claim 3, characterized in that, The preset temperature range is 500℃ to 700℃, and the preset duration is 3 minutes to 10 minutes.

6. The method for detecting subsurface defects in steel according to any one of claims 1 to 5, characterized in that, The process of performing subsurface defect detection at the location of defect B to obtain the subsurface defect detection result of the steel to be inspected includes: A metallographic sample is inlaid at the location of defect B, followed by grinding to remove the surface coating or metal substrate at the location of defect B, and then polishing is performed. Subsurface defect information was obtained by detecting the location of the B defect after polishing using a microscope. Based on the subsurface defect information, the subsurface defect detection result is determined.

7. The method for detecting subsurface defects in steel according to claim 6, characterized in that, The process of detecting subsurface defects at the location of defect B after polishing using a microscope to obtain subsurface defect information includes: The B defect location was analyzed for composition and morphology using an electron microscope. Based on the compositional analysis results at the location of defect B, determine the composition of the components at the location of defect B; The step of determining the subsurface defect detection result based on the subsurface defect information includes: Based on the composition of the components at the location of defect B, the defect type and cause are determined.

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