Steel detection method and device, electronic equipment and storage medium

Abstract

The invention provides a steel detection method and device, electronic equipment and a storage medium, and relates to the field of material analys.Firstly, the surface of steel subjected to inclusion corrosion treatment is coated with a preset material, heating is conducted, as inclusion in the steel can be corroded through inclusion corrosion treatment, defects are generated on the surface of the steel, and the surface of the steel is detected; therefore, the preset material is filled at the defect position, caused by inclusion corrosion, of the steel surface after coating heating treatment, then image acquisition treatment is conducted on the steel surface after coating heating treatment, a steel surface image is acquired and recognized, and whether the defect caused by inclusion corrosion exists on the steel surface or not is determined. And determining whether the inclusions exist in the steel. According to the embodiment, automatic detection of the inclusions in the steel can be realized by using the steel surface image, and the detection precision and efficiency of the inclusions in the steel are greatly improved, so that the material performance can be further improved, and the quality risk is reduced.

Description

Technical Field

[0001] The present invention relates to the field of material analysis, and in particular to a steel material detection method, device, electronic equipment and storage medium. Background Art

[0002] Marine engineering steel is a special steel designed specifically for marine engineering environments. It needs to cope with the erosion of multiple factors in the marine environment, such as salt spray, humidity, and wave impact, so it must have higher corrosion resistance.

[0003] Inclusions, as the main source of pitting corrosion in steel, have a huge impact on the corrosion resistance of steel. Inclusions produce pitting pits at their locations through synergistic effects with other corrosive ions, galvanic corrosion, micro-crevice corrosion and chemical dissolution, which often lead to reduced dimensional accuracy of workpieces, perforation of equipment pipe walls and aggravation of stress corrosion cracking.

[0004] Therefore, there is an urgent need for a detection method to improve the detection accuracy of inclusions in offshore steel, enhance material properties, and reduce quality risks. Summary of the invention

[0005] The embodiments of the present invention provide a steel material detection method, device, electronic equipment and storage medium to solve the problem of low detection accuracy of inclusions in steel materials.

[0006] In a first aspect, an embodiment of the present invention provides a steel material detection method, comprising: The surface of the steel material after the inclusion corrosion treatment is coated and heated with a preset material so that the surface defects of the steel material are filled with the preset material; wherein the preset material has photothermal properties and component specificity; Performing image acquisition processing on the surface of the steel material after the coating and heating treatment to obtain a steel material surface image; wherein the steel material surface image includes one or more of an optical image, a thermal image, and an element distribution image; Based on the steel surface image, it is determined whether the steel has inclusions.

[0007] In a possible implementation, the steel surface image includes the optical image, the thermal image, and the element distribution map; The determining whether the steel has inclusions based on the steel surface image includes: The optical image, the thermal image and the element distribution map are superimposed to obtain a composite image of the steel surface; wherein the optical image, the thermal image and the element distribution map correspond to the same steel surface area; According to the synthesized image, it is determined whether the steel material has inclusions.

[0008] In a possible implementation, the preset material is a hydrogel material, and the hydrogel material includes gold nanoparticles and an organic photothermal dye; The optical image is used to record the optical characteristic image of the steel surface and the organic photothermal dye filled in the defects on the steel surface, and the color channel of the pixel point in the optical characteristic image of the organic photothermal dye is the first preset color channel; The thermal imaging image is used to record the temperature distribution image of the steel surface and the hydrogel material filled in the defects on the steel surface, and the color channel of the pixel points in the temperature distribution image of the hydrogel material is the second preset color channel; The element distribution map is used to record the element distribution characteristic images of the steel surface and the gold nanoparticles filled in the defects on the steel surface, and the color channel of the pixel points in the element distribution characteristic image of the gold nanoparticles is the third preset color channel; The first preset color channel, the second preset color channel, and the third preset color channel are different.

[0009] In a possible implementation, determining whether the steel material has inclusions according to the composite image includes: Acquire a color channel of each pixel in the composite image; wherein the color channel of each pixel in the composite image is obtained by superimposing the color channels of corresponding pixels in the thermal image, the optical image, and the element distribution map channel by channel; Detecting whether there are pixels of a fourth preset color channel in the composite image; wherein the fourth preset color channel is determined based on the superposition of the first preset color channel, the second preset color channel, and the third preset color channel; If it is detected that there are pixels of the fourth preset color channel in the composite image, it is determined that the steel has inclusions; otherwise, it is determined that the steel has no inclusions.

[0010] In a possible implementation, after determining whether the steel has inclusions, the method further includes: If the steel has inclusions, determining the quality index of the steel according to the distribution of the inclusions in the steel; Based on the quality indicators, the production process of the steel is optimized.

[0011] In a possible implementation, the method of applying a preset material to the surface of the steel after the inclusion corrosion treatment and heating it so that the surface defects of the steel are filled with the preset material includes: Controlling the coating device to coat the preset material on the surface of the steel material after the inclusion corrosion treatment; Controlling the near-infrared light heating device to irradiate the surface of the steel material so as to heat up and liquefy the preset material on the surface of the steel material; The mechanical scraping device is controlled to scrape off excess preset material on the surface of the steel material, so that the defects on the surface of the steel material are filled with the heated and liquefied preset material.

[0012] In a possible implementation, before applying a predetermined material to heat the surface of the steel after the inclusion corrosion treatment, the method further includes: Immersing the steel in a pre-configured corrosive solution, and based on preset corrosion parameters, controlling the surface of the steel to chemically react with the corrosive solution to corrode inclusions, thereby obtaining steel treated with inclusion corrosion; Wherein, the pre-configured etching solution includes hydrochloric acid, ferric chloride and sodium chloride, and the inclusions are non-metallic inclusions.

[0013] In a second aspect, an embodiment of the present invention provides a steel material detection device, comprising: The first processing unit is used to apply a preset material to the surface of the steel after the inclusion corrosion treatment, and then heat the surface of the steel to fill the surface defects of the steel with the preset material; wherein the preset material has photothermal properties and component specificity; An acquisition unit is used to perform image acquisition processing on the surface of the steel material after the coating and heating treatment to obtain a steel material surface image; wherein the steel material surface image includes one or more of an optical image, a thermal image, and an element distribution image; The second processing unit is used to determine whether the steel has inclusions based on the steel surface image.

[0014] In a third aspect, an embodiment of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the steel detection method as described in the first aspect or any possible implementation method of the first aspect are implemented.

[0015] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the steel detection method as described in the first aspect or any possible implementation of the first aspect are implemented.

[0016] The embodiment of the present invention provides a steel detection method, device, electronic device and storage medium. First, a preset material is applied to the surface of the steel after the inclusion corrosion treatment and heated. Since the inclusion corrosion treatment can corrode the inclusions in the steel, causing defects on the steel surface, the defects on the steel surface caused by the inclusion corrosion after the coating and heating treatment are filled with the preset material. Then, the steel surface after the coating and heating treatment is imaged and processed to collect the steel surface image, and identify the steel surface image to determine whether there are defects on the surface caused by the corrosion of the inclusions, that is, to determine whether there are inclusions in the steel. This embodiment can realize the automatic detection of inclusions in the steel by using the steel surface image, and highlight the defects on the steel surface in the steel surface image by using the photothermal characteristics and / or component specificity of the preset material, which greatly improves the detection accuracy of inclusions in the steel, thereby further improving the material performance and reducing quality risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 work.

[0018] Figure 1 is a flow chart of an implementation of a steel material detection method provided by an embodiment of the present invention; Figure 2 is a flow chart of another steel material detection method provided by an embodiment of the present invention; Figure 3 is a structural schematic diagram of a steel material detection device provided by an embodiment of the present invention; Figure 4 is a schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0020] Inclusions are the main source of pitting corrosion in steel. The presence of inclusions may change the electrochemical properties of the steel surface, making it more susceptible to local corrosion, such as pitting corrosion, etc., and because corrosion products often cover pitting pits, making them difficult to detect, they are very likely to cause sudden accidents, and are one of the most dangerous and destructive types of corrosion. In addition, inclusions produce pitting pits at their locations through the synergistic effect of other corrosive ions, galvanic corrosion, micro-crevice corrosion, and chemical dissolution, which often lead to reduced dimensional accuracy of workpieces, perforation of equipment pipe walls, and increased stress corrosion cracking. Therefore, it is necessary to improve the detection accuracy of inclusions in steel and detect inclusions in a timely manner so that improvements can be made in a timely manner to avoid affecting the performance of the workpiece and causing safety accidents.

[0021] In an embodiment of the present invention, a preset material is firstly coated on the surface of the steel after the inclusion corrosion treatment and heated. Since the inclusion corrosion treatment can corrode the inclusions in the steel, so that defects caused by the inclusions are generated on the surface of the steel, the defects caused by the inclusion corrosion on the surface of the steel after the coating and heating treatment are filled with the preset material, and then the steel surface after the coating and heating treatment is imaged and processed to collect the steel surface image. This embodiment utilizes the photothermal characteristics or component specificity of the preset material to highlight the defects on the steel surface in the steel surface image, and finally identifies the steel surface image to determine whether there are inclusions in the steel.

[0022] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0023] Figure 1 A flow chart of a steel material detection method provided by an embodiment of the present invention is described in detail as follows: Step 101, using a preset material to apply a coating and heating treatment to the surface of the steel after the inclusion corrosion treatment, so that the preset material is filled in the surface defects of the steel; wherein the preset material has photothermal properties and component specificity.

[0024] Exemplarily, this embodiment calculates the amount of various chemical reagents required based on the material and corrosion requirements of the steel. The corrosive liquid is pre-configured through an automated metering device. The pre-configured corrosive liquid is then used to corrode the surface of the steel. For example, the steel to be corroded is accurately transported to the corrosion work area with the help of automated equipment; various corrosion parameters are pre-set in the automated control system, such as corrosion time, corrosion liquid temperature, stirring speed, etc. The automated control system then regulates the subsequent corrosion process based on these set corrosion parameters.

[0025] Among them, this embodiment can detect and identify one or more inclusions, and it is only necessary to configure the corrosion liquid reasonably for the inclusions.

[0026] This embodiment does not limit the type of steel, and it can be marine engineering steel, etc.

[0027] After inclusion corrosion treatment, defects such as pits caused by inclusion corrosion will be exposed on the steel surface. Therefore, in this embodiment, after the surface of the steel after inclusion corrosion treatment is coated and heated with a preset material, the defects on the steel surface will be filled with the preset material.

[0028] Step 102, performing image acquisition processing on the surface of the steel material after the coating and heating treatment to obtain a steel material surface image; wherein the steel material surface image includes one or more of an optical image, a thermal imaging image, and an element distribution image.

[0029] Exemplarily, since the preset material has photothermal properties and cost specificity, in order to realize automatic identification of whether there are defects on the steel surface caused by corrosion of inclusions, this embodiment firstly collects images of the steel surface after coating and heat treatment, and obtains one or more of the optical image, thermal image and element distribution map.

[0030] Among them, since the preset material has photothermal characteristics and cost specificity, the optical image records the optical characteristic images of the steel surface and the preset material filled in the defects on the steel surface; the thermal imaging image records the temperature distribution image of the steel surface and the preset material filled in the defects on the steel surface; the element distribution map records the element distribution characteristic image of the steel surface and the preset material filled in the defects on the steel surface.

[0031] The element distribution map may be an EDS surface scan map, which can be obtained by energy-dispersive X-ray spectroscopy (EDS) surface scan. In the surface scan mode, EDS scans a surface on the sample surface to obtain element distribution information of the entire area.

[0032] Step 103: Determine whether the steel has inclusions based on the steel surface image.

[0033] Exemplarily, this embodiment automatically identifies one or more of the acquired optical images, thermal images, and element distribution maps to determine defects caused by corrosion of inclusions, and further determine whether the steel has inclusions.

[0034] In a feasible implementation manner, this embodiment can use a pre-trained image recognition model to identify the collected image and determine whether there are defects on the steel surface in the image caused by corrosion of inclusions.

[0035] In another feasible implementation manner, the present embodiment can also utilize the photothermal characteristics and component specificity of a preset material to analyze the distinguishing characteristic points in the optical image, thermal image, and element distribution map to determine the defects caused by the corrosion of inclusions.

[0036] In summary, this embodiment provides a steel material detection method, which specifically relates to the field of analyzing materials by measuring the chemical properties of materials. First, a preset material is applied to the surface of the steel material after the inclusion corrosion treatment, and then heated. Since the inclusion corrosion treatment can corrode the inclusions in the steel material, causing defects on the steel surface, the defects on the steel surface caused by the inclusion corrosion after the coating and heating treatment are filled with the preset material. Then, the steel surface after the coating and heating treatment is imaged and processed, and the steel surface image is collected and the steel surface image is identified to determine whether there are defects on the steel surface caused by the corrosion of the inclusions, that is, to determine whether there are inclusions in the steel. This embodiment can realize the automatic detection of inclusions in the steel by using the steel surface image, and highlight the defects on the steel surface in the steel surface image by using the photothermal characteristics and / or component specificity of the preset material, which greatly improves the detection accuracy of inclusions in the steel, thereby further improving the material performance and reducing quality risks.

[0037] In order to more accurately corrode inclusions, the present embodiment uses a prepared corrosive solution including hydrochloric acid, ferric chloride and sodium chloride to react chemically with the steel, and controls the corrosion process based on preset corrosion parameters to achieve accurate corrosion of inclusions in the steel; and in order to highlight the characteristics of the surface defects of the steel, the present embodiment uses a hydrogel material including gold nanoparticles and organic photothermal dyes to coat the surface of the steel, and controls the near-infrared heating device to irradiate the coated steel surface, so that the liquefied hydrogel material can more closely fill the surface defects of the steel, thereby improving the detection accuracy. Since the hydrogel material including gold nanoparticles and organic photothermal dyes has photothermal properties and component specificity, the present embodiment collects optical images, thermal imaging maps and element distribution maps of the steel surface after the coating and heating treatment, through the optical characteristic images of the steel surface and the organic photothermal dye filled in the defects of the steel surface in the optical image, the temperature distribution images of the steel surface and the hydrogel material filled in the defects of the steel surface in the thermal imaging map, and the element distribution characteristic images of the steel surface and the gold nanoparticles filled in the defects of the steel surface in the element distribution map. Different images are used to highlight the characteristics of surface defects in steel, further improving the accuracy of inclusion detection.

[0038] Figure 2 Another implementation flow chart of a steel material detection method provided by an embodiment of the present invention is described in detail as follows: Step 201, immersing the steel material in a pre-configured corrosion solution, and based on preset corrosion parameters, controlling the chemical reaction between the steel material surface and the corrosion solution to corrode inclusions, thereby obtaining the steel material after the inclusion corrosion treatment.

[0039] The pre-configured etching solution includes hydrochloric acid, ferric chloride and sodium chloride, and the inclusions are non-metallic inclusions.

[0040] Exemplarily, the inclusions may be non-metallic inclusions, such as sulfides, manganese sulfide (MnS). Since the pitting corrosion resistance of steel decreases with increasing Cl- concentration, MnS is susceptible to corrosion by chloride solutions. Therefore, this embodiment designs a corrosive solution containing hydrochloric acid (HCl), ferric chloride (FeCl), and sodium chloride (NaCl).

[0041] In one example, the present embodiment prepares a mixed corrosion solution at room temperature (20 degrees Celsius-25 degrees Celsius), wherein the concentration of hydrochloric acid is 1 mol / L, the concentration of ferric chloride solution is 0.3 mol / L, and the concentration of sodium chloride solution is 4 mol / L. Such a concentration combination can limit excessive corrosion of the steel substrate by controlling the time while exerting their respective corrosion effects.

[0042] a) The first stage of corrosion (0-30 minutes) In the first 30 minutes after the corrosion begins, ferric chloride and sodium chloride work together. Ferric chloride, as an oxidant, will cause the iron on the surface of the steel to undergo an oxidation reaction. At the same time, the chloride ions in the sodium chloride solution will destroy the passivation film on the steel surface, and due to the change in the local electrochemical environment around the MnS inclusions, corrosion will begin to occur around them. At this stage, due to the relatively low concentration of hydrochloric acid, its rapid dissolution effect on the steel matrix is ​​not obvious.

[0043] b) Second stage of corrosion (30-90 minutes) As time passes to 30-90 minutes, hydrochloric acid begins to play a more important role. Since the steel matrix around the MnS inclusions in the previous stage is already in a relatively active corrosion state, hydrochloric acid will accelerate the corrosion of this part. At this time, ferric chloride continues to oxidize the iron on the steel surface, while the chloride ions in the sodium chloride continue to destroy the passivation film and promote corrosion around the MnS inclusions. By paying close attention to the corrosion process, at the end of this stage, it can be achieved that the MnS inclusions and their surroundings are corroded, while other parts of the steel matrix will not be corroded too much.

[0044] Step 202, using a preset material to apply a coating and heating treatment to the surface of the steel after the inclusion corrosion treatment, so that the preset material is filled in the surface defects of the steel; wherein the preset material has photothermal properties and component specificity.

[0045] In a feasible implementation manner, step 202 includes: The coating device is controlled to coat the preset material on the surface of the steel material after the inclusion corrosion treatment.

[0046] The near-infrared light heating device is controlled to irradiate the surface of the steel material so as to heat up and liquefy the preset material on the surface of the steel material.

[0047] The mechanical scraping device is controlled to scrape off the excess preset material on the surface of the steel material, so that the defects on the surface of the steel material are filled with the heated and liquefied preset material.

[0048] For example, after inclusion corrosion treatment, defects such as pits caused by corrosion of inclusions will be exposed on the surface of the steel. Therefore, in this embodiment, after the surface of the steel after inclusion corrosion treatment is coated and heated with a preset material, the defects on the surface of the steel will be filled with the preset material.

[0049] In a feasible implementation, the preset material has photothermal properties and component specificity. That is, the preset material includes a specific component, which makes the preset material have photothermal properties. The preset material with photothermal properties in this embodiment can be fully liquefied after heating, such as heating by near-infrared light irradiation. At this time, due to the pre-treatment of inclusion corrosion, a cavity is generated near the inclusion, which can be used as a storage position for the liquefied preset material.

[0050] In a feasible implementation, in order to effectively distinguish the defective parts of the steel surface from the normal parts of the steel surface, a mechanical scraping device (scraper, scraper, etc.) can be used to scrape away the excess preset material after liquefaction on the steel surface.

[0051] In one example, this embodiment selects automated coating equipment, such as a sprayer, a blade coater, or a spin coater. According to the shape of the steel and the coating requirements, the equipment parameters are adjusted to ensure that the preset material can be evenly coated on the surface of the steel. After the coating process, a near-infrared light source with precisely controlled power and irradiation time, such as a near-infrared lamp or a laser generator, is used, and an automated optical path adjustment system is provided to ensure that the near-infrared light can be evenly and stably irradiated on the surface of the steel coated with the preset material.

[0052] Step 203, performing image acquisition processing on the surface of the steel material after the coating and heating treatment to obtain a steel material surface image; wherein the steel material surface image includes one or more of an optical image, a thermal imaging image, and an element distribution image.

[0053] Among them, the preset material is a hydrogel material, which includes gold nanoparticles and organic photothermal dyes.

[0054] The optical image is used to record the optical characteristic image of the steel surface and the organic photothermal dye filled in the defects on the steel surface. The color channel of the pixel point in the optical characteristic image of the organic photothermal dye is the first preset color channel.

[0055] The thermal imaging image is used to record the temperature distribution image of the steel surface and the hydrogel material filled in the defects on the steel surface. The color channel of the pixel point in the temperature distribution image of the hydrogel material is the second preset color channel.

[0056] The element distribution map is used to record the element distribution characteristic images of the steel surface and the gold nanoparticles filled in the defects on the steel surface. The color channel of the pixel points in the element distribution characteristic image of the gold nanoparticles is the third preset color channel.

[0057] The first preset color channel, the second preset color channel, and the third preset color channel are different.

[0058] Exemplarily, the preset material in this embodiment may be a polyvinyl alcohol hydrogel including gold nanoparticles and an organic photothermal dye.

[0059] In a possible implementation, after scraping off excess gel on the steel surface, a thermal image is collected. Because near-infrared light heating causes the gel temperature to rise while the material matrix temperature does not change much, the temperature of the steel surface defect filled with polyvinyl alcohol hydrogel in the thermal image is higher than the steel matrix temperature; after scraping off excess gel on the steel surface, an optical image is collected. Because polyvinyl alcohol hydrogel is doped with organic photothermal dyes, which will obtain different colors after heating, the steel surface defects filled with polyvinyl alcohol hydrogel in the optical image show a specific color different from the steel matrix, namely, the color of the organic photothermal dye; after scraping off excess gel on the steel surface, an element distribution map is collected. Because polyvinyl alcohol hydrogel is doped with gold nanoparticles, which has a different composition from the steel matrix, gold elements are aggregated at the steel surface defects filled with polyvinyl alcohol hydrogel in the element distribution map.

[0060] The color channel of the pixel in the optical characteristic image of the organic photothermal dye is the first preset color channel, so the color channel of the steel surface defect in the optical image is the first preset color channel. In addition, in the optical image, the color channels of the remaining pixel points except the corresponding pixel points of the organic photothermal dye are other color channels except the first preset color channel, the second preset color channel and the third preset color channel.

[0061] In this embodiment, the color channel of the pixel corresponding to the hydrogel material in the thermal image is mapped to the second preset color channel, so the color channel of the steel surface defect in the thermal image is the second preset color channel. In addition, in the thermal image, the color channels of the remaining pixel points except the pixel corresponding to the hydrogel material are other color channels except the first preset color channel, the second preset color channel and the third preset color channel.

[0062] In this embodiment, the color channel of the pixel corresponding to the gold element in the element distribution map is mapped to the third preset color channel. Therefore, the color channel of the steel surface defect in the element distribution map is the third preset color channel. In addition, in the element distribution map, the color channels of the remaining pixel points except the pixel corresponding to the gold element are other color channels except the first preset color channel, the second preset color channel and the third preset color channel.

[0063] Step 204, the steel surface image includes an optical image, a thermal image and an element distribution map; the optical image, the thermal image and the element distribution map are superimposed to obtain a composite image of the steel surface; wherein the optical image, the thermal image and the element distribution map correspond to the same steel surface area.

[0064] Exemplarily, in this embodiment, in order to ensure the accuracy of detection, the sizes of the optical image, the thermal image, and the element distribution map, as well as the corresponding steel surface areas, are all the same.

[0065] In order to improve the detection accuracy, the steel surface image in this embodiment includes an optical image, a thermal image and an element distribution map.

[0066] Step 205: Determine whether the steel material has inclusions based on the synthesized image.

[0067] In a feasible implementation manner, step 205 includes the following steps: The color channel of each pixel in the composite image is obtained by superimposing the color channels of the corresponding pixel in the thermal image, the optical image and the element distribution map.

[0068] Detect whether there are pixels of a fourth preset color channel in the composite image; wherein the fourth preset color channel is determined based on the superposition of the first preset color channel, the second preset color channel, and the third preset color channel.

[0069] If the pixel point of the fourth preset color channel exists in the detected composite image, it is determined that the steel has inclusions; otherwise, it is determined that the steel has no inclusions.

[0070] Exemplarily, since the color channel of each pixel in the composite image is obtained by superimposing the color channels of the corresponding pixel in the thermal image, the optical image, and the element distribution map, each pixel in the composite image is traversed and detected, if there is a pixel whose color channel is the fourth preset color channel, wherein the fourth preset color channel is determined based on the superposition of the first preset color channel, the second preset color channel, and the third preset color channel, it is determined that there are defects on the surface of the steel material due to corrosion of inclusions, that is, the steel material has inclusions, otherwise, it is determined that the steel material has no inclusions.

[0071] In a feasible implementation, the composite image is obtained by superimposing the thermal image, the optical image and the element distribution map in a certain proportion, and the fourth preset color channel is determined by adding the first preset color channel, the second preset color channel and the third preset color channel in this proportion.

[0072] Step 206: If the steel has inclusions, the quality index of the steel is determined according to the distribution of the inclusions in the steel.

[0073] For example, if there are pixels in the composite image whose color channel is the fourth preset color channel, the size, shape, etc. of the inclusions can be estimated or calculated based on the position and distribution of the pixels in the composite image whose color channel is the fourth preset color channel, and then the quality indicators of the steel can be determined according to the quality standards.

[0074] Step 207, optimizing the production process of the steel based on the quality index.

[0075] Exemplarily, this embodiment guides the optimization of process steps that may cause inclusions to be generated in steel based on the determined quality indicators, so as to improve the quality indicators of the steel.

[0076] In summary, the present embodiment uses a prepared corrosion solution including hydrochloric acid, ferric chloride and sodium chloride to react chemically with the steel, and controls the corrosion process based on preset corrosion parameters, so as to achieve precise corrosion of inclusions in the steel; the present embodiment uses a hydrogel material including gold nanoparticles and an organic photothermal dye to coat the surface of the steel, and controls a near-infrared heating device to irradiate the coated steel surface, so that the liquefied hydrogel material can fill the surface defects of the steel more closely. Since the hydrogel material including gold nanoparticles and the organic photothermal dye has photothermal properties and component specificity, the present embodiment collects optical images, thermal imaging maps and element distribution maps of the steel surface after the coating and heating treatment. Through the optical characteristic images of the steel surface and the organic photothermal dye filled in the defects of the steel surface in the optical image, the temperature distribution images of the steel surface and the hydrogel material filled in the defects of the steel surface in the thermal imaging map, and the element distribution characteristic images of the steel surface and the gold nanoparticles filled in the defects of the steel surface in the element distribution map, the characteristics of the defects on the steel surface are highlighted by using a variety of images, so as to further improve the accuracy of inclusion detection.

[0077] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0078] The following is an embodiment of the device of the present invention. For details not described in detail, reference may be made to the corresponding method embodiments described above.

[0079] Figure 3 The structural schematic diagram of the steel material detection device provided by the embodiment of the present invention is shown. For the convenience of description, only the part related to the embodiment of the present invention is shown, which is described in detail as follows: like Figure 3 As shown, the steel material detection device 300 includes: The first processing unit 301 is used to apply a coating and heating treatment to the surface of the steel after the inclusion corrosion treatment with a preset material so that the surface defects of the steel are filled with the preset material; wherein the preset material has photothermal properties and component specificity.

[0080] The acquisition unit 302 is used to perform image acquisition processing on the surface of the steel after the coating and heating treatment to obtain a steel surface image; wherein the steel surface image includes one or more of an optical image, a thermal image, and an element distribution image.

[0081] The second processing unit 303 is used to determine whether the steel has inclusions based on the steel surface image.

[0082] In a possible implementation, the steel surface image includes an optical image, a thermal image, and an element distribution map; the second processing unit 303 is specifically used for: The optical image, thermal image and element distribution map are superimposed to obtain a composite image of the steel surface; wherein the optical image, thermal image and element distribution map correspond to the same steel surface area.

[0083] Based on the composite image, determine whether the steel has inclusions.

[0084] In a possible implementation, the preset material is a hydrogel material, and the hydrogel material includes gold nanoparticles and organic photothermal dyes.

[0085] The optical image is used to record the optical characteristic image of the steel surface and the organic photothermal dye filled in the defects on the steel surface. The color channel of the pixel point in the optical characteristic image of the organic photothermal dye is the first preset color channel.

[0086] The thermal imaging image is used to record the temperature distribution image of the steel surface and the hydrogel material filled in the defects on the steel surface, and the color channel of the pixel point in the temperature distribution image of the hydrogel material is the second preset color channel; The element distribution map is used to record the element distribution characteristic images of the steel surface and the gold nanoparticles filled in the defects on the steel surface. The color channel of the pixel points in the element distribution characteristic image of the gold nanoparticles is the third preset color channel.

[0087] The first preset color channel, the second preset color channel, and the third preset color channel are different.

[0088] In a possible implementation, the second processing unit 303 is further configured to: The color channel of each pixel in the composite image is obtained by superimposing the color channels of the corresponding pixel in the thermal image, the optical image and the element distribution map.

[0089] Detect whether there are pixels of a fourth preset color channel in the composite image; wherein the fourth preset color channel is determined based on the superposition of the first preset color channel, the second preset color channel, and the third preset color channel.

[0090] If the pixel point of the fourth preset color channel exists in the detected composite image, it is determined that the steel has inclusions; otherwise, it is determined that the steel has no inclusions.

[0091] In a possible implementation, the steel inspection device 300 further includes: a third processing unit, which is specifically used to: if the steel has inclusions, determine the quality index of the steel according to the distribution of the inclusions in the steel; and optimize the production process of the steel based on the quality index.

[0092] In a possible implementation, the first processing unit 301 is specifically configured to: The coating device is controlled to coat the preset material on the surface of the steel material after the inclusion corrosion treatment.

[0093] The near-infrared light heating device is controlled to irradiate the surface of the steel material so as to heat up and liquefy the preset material on the surface of the steel material.

[0094] The mechanical scraping device is controlled to scrape off the excess preset material on the surface of the steel material, so that the defects on the surface of the steel material are filled with the heated and liquefied preset material.

[0095] In a possible implementation, before the first processing unit 301, the steel detection device 300 also includes a fourth processing unit, which is specifically used to: immerse the steel in a pre-configured corrosive liquid, and based on preset corrosion parameters, control the chemical reaction between the steel surface and the corrosive liquid to corrode inclusions, and obtain the steel after the inclusion corrosion treatment; wherein the pre-configured corrosive liquid includes hydrochloric acid, ferric chloride and sodium chloride, and the inclusions are non-metallic inclusions.

[0096] Figure 4 Schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 4 As shown, the electronic device 4 of this embodiment includes: a processor 40 and a memory 41. The memory 41 is used to store a computer program 42, and the processor 40 is used to call and run the computer program 42 stored in the memory 41 to execute the steps in the above-mentioned various steel detection method embodiments, such as Figure 1Alternatively, the processor 40 is used to call and run the computer program 42 stored in the memory 41 to implement the functions of each module / unit in the above-mentioned device embodiments, such as Figure 3 The functions of each unit are shown.

[0097] Exemplarily, the computer program 42 may be divided into one or more modules / units, one or more modules / units are stored in the memory 41 and executed by the processor 40 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program 42 in the electronic device 4. For example, the computer program 42 may be divided into Figure 3 The individual units shown.

[0098] The electronic device 4 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The electronic device 4 may include, but is not limited to, a processor 40 and a memory 41. Those skilled in the art will appreciate that Figure 4 It is only an example of the electronic device 4 and does not constitute a limitation of the electronic device 4. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0099] The processor 40 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0100] The memory 41 may be an internal storage unit of the electronic device 4, such as a hard disk or memory of the electronic device 4. The memory 41 may also be an external storage device of the electronic device 4, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 4. Further, the memory 41 may also include both an internal storage unit and an external storage device of the electronic device 4. The memory 41 is used to store computer programs and other programs and data required by the electronic device. The memory 41 may also be used to temporarily store data that has been output or is to be output.

[0101] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0102] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0103] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0104] In the embodiments provided by the present invention, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are only schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0105] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0106] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0107] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, the steps of the above-mentioned steel detection method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electric carrier signals and telecommunication signals.

[0108] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A steel material detection method, characterized in that: The method comprises: The surface of the steel material after the inclusion corrosion treatment is coated and heated with a preset material so that the surface defects of the steel material are filled with the preset material; wherein the preset material has photothermal properties and component specificity; Performing image acquisition processing on the surface of the steel material after the coating and heating treatment to obtain a steel material surface image; wherein the steel material surface image includes one or more of an optical image, a thermal image, and an element distribution image; Based on the steel surface image, it is determined whether the steel has inclusions.

2. The steel material detection method according to claim 1, characterized in that: The steel surface image includes the optical image, the thermal image and the element distribution map; The determining whether the steel has inclusions based on the steel surface image includes: The optical image, the thermal image and the element distribution map are superimposed to obtain a composite image of the steel surface; wherein the optical image, the thermal image and the element distribution map correspond to the same steel surface area; According to the synthesized image, it is determined whether the steel material has inclusions.

3. The steel material detection method according to claim 2, characterized in that: The preset material is a hydrogel material, and the hydrogel material includes gold nanoparticles and organic photothermal dyes; The optical image is used to record the optical characteristic image of the steel surface and the organic photothermal dye filled in the defects on the steel surface, and the color channel of the pixel point in the optical characteristic image of the organic photothermal dye is the first preset color channel; The thermal imaging image is used to record the temperature distribution image of the steel surface and the hydrogel material filled in the defects on the steel surface, and the color channel of the pixel points in the temperature distribution image of the hydrogel material is the second preset color channel; The element distribution map is used to record the element distribution characteristic images of the steel surface and the gold nanoparticles filled in the defects on the steel surface, and the color channel of the pixel points in the element distribution characteristic image of the gold nanoparticles is the third preset color channel; The first preset color channel, the second preset color channel, and the third preset color channel are different.

4. The steel material detection method according to claim 3, characterized in that: Determining whether the steel material has inclusions according to the synthesized image includes: Acquire a color channel of each pixel in the composite image; wherein the color channel of each pixel in the composite image is obtained by superimposing the color channels of corresponding pixels in the thermal image, the optical image, and the element distribution map channel by channel; Detecting whether there are pixels of a fourth preset color channel in the composite image; wherein the fourth preset color channel is determined based on the superposition of the first preset color channel, the second preset color channel, and the third preset color channel; If it is detected that there are pixels of the fourth preset color channel in the composite image, it is determined that the steel has inclusions; otherwise, it is determined that the steel has no inclusions.

5. The steel material detection method according to any one of claims 1 to 4, characterized in that: After determining whether the steel has inclusions, the method further includes: If the steel has inclusions, determining the quality index of the steel according to the distribution of the inclusions in the steel; Based on the quality indicators, the production process of the steel is optimized.

6. The steel material detection method according to any one of claims 1 to 4, characterized in that: The method of applying a predetermined material to the surface of the steel after the inclusion corrosion treatment and heating it so that the surface defects of the steel are filled with the predetermined material comprises: Controlling the coating device to coat the preset material on the surface of the steel material after the inclusion corrosion treatment; Controlling the near-infrared light heating device to irradiate the surface of the steel material so as to heat up and liquefy the preset material on the surface of the steel material; The mechanical scraping device is controlled to scrape off excess preset material on the surface of the steel material, so that the defects on the surface of the steel material are filled with the heated and liquefied preset material.

7. The steel material detection method according to any one of claims 1 to 4, characterized in that: Before applying a coating and heating treatment on the surface of the steel material after the inclusion corrosion treatment using a preset material, the method further comprises: Immersing the steel in a pre-configured corrosive solution, and based on preset corrosion parameters, controlling the surface of the steel to chemically react with the corrosive solution to corrode inclusions, thereby obtaining steel treated with inclusion corrosion; Wherein, the pre-configured etching solution includes hydrochloric acid, ferric chloride and sodium chloride, and the inclusions are non-metallic inclusions.

8. A steel material detection device, characterized in that: The device comprises: The first processing unit is used to apply a preset material to the surface of the steel after the inclusion corrosion treatment, and then heat the surface of the steel to fill the surface defects of the steel with the preset material; wherein the preset material has photothermal properties and component specificity; An acquisition unit is used to perform image acquisition processing on the surface of the steel material after the coating and heating treatment to obtain a steel material surface image; wherein the steel material surface image includes one or more of an optical image, a thermal image, and an element distribution image; The second processing unit is used to determine whether the steel has inclusions based on the steel surface image.

9. An electronic device, characterized in that: It comprises a processor and a memory, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute the steel detection method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steel material detection method according to any one of claims 1 to 7 is implemented.

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