A method of inclusions analysis based on steel material and related apparatus

Abstract

Embodiments of the present application provide a steel material-based inclusion analysis method and related equipment, which acquires brightness information of a target sample and a standard detection object by image acquisition, establishes a brightness value quantization standard based on the brightness information of the target sample and the standard detection object and a standard brightness of the target sample and the standard detection object, determines the type and position of inclusions by inclusion analysis on the brightness value, establishes a brightness quantization standard under the current image acquisition environment through the brightness information of the target sample and the standard detection object, and further determines the brightness distribution information of the surface of the target sample, classifies inclusions through the brightness value of the inclusion and the first current brightness of the target sample, and determines the type of the inclusion according to the classification, which can further improve the accuracy of inclusion analysis, thereby reducing the analysis difficulty and improving the analysis efficiency.

Description

Technical Field

[0001] This invention relates to the field of metal inclusion detection technology, and in particular to an inclusion analysis method and related equipment based on steel materials. Background Technology

[0002] With the development of metal smelting technology, rare earth and heavy metal elements have begun to be introduced into steel smelting. On the one hand, as alloying elements, the addition of elements such as tungsten can improve the wear resistance of steel, the addition of antimony can improve the weather resistance of steel, and the addition of rare earth elements such as lanthanides and cerium can purify the steel, remove impurities and microalloying, thereby improving the fatigue performance of steel and reducing cracks. On the other hand, the oxides and carbonates of lanthanides, cerium, barium and other elements can be used as tracers to track the source of inclusions and surface defects in steel.

[0003] Adding rare earth elements and heavy metals during steelmaking can create inclusions, affecting the steel's properties. Currently, inclusion detection in steel materials is typically achieved through manual observation. However, when using a conventional scanning electron microscope (SEM) for inclusion analysis, it's necessary to move the field of view sequentially at a certain magnification, searching for inclusions in each field, and then performing size, location, and composition analysis. This process is labor-intensive, prone to human error, and easily misses inclusions. Therefore, current methods for detecting inclusions in steel materials suffer from low accuracy, high throughput, long detection time, and high labor costs. Summary of the Invention

[0004] This invention provides a method and related equipment for analyzing inclusions in steel materials, in order to solve the problems of low accuracy, large detection volume, long detection time, and high labor costs associated with current manual methods for detecting inclusions.

[0005] In a first aspect, the present invention provides a method for inclusion analysis based on steel materials, comprising:

[0006] Image information of a target sample and a standard analyte is acquired, wherein the standard analyte is set within a preset range of the target sample, and the image information includes brightness value distribution information in the image;

[0007] A first standard brightness of the target sample and a second standard brightness of the standard test object are obtained, wherein the first standard brightness is the brightness value of the target sample surface obtained by placing the target sample in a standard brightness environment, and the second standard brightness is the brightness value of the standard test object surface obtained by placing the target sample in a standard brightness environment.

[0008] Based on the brightness value distribution information, determine the first current brightness of the target sample in the image information and the second current brightness of the standard test object in the image information;

[0009] Based on the first current brightness, the second current brightness, the first standard brightness, and the second standard brightness, the distribution of the first inclusion on the surface of the target sample is determined. The distribution of the first inclusion includes the type of inclusion and its relative position in the target sample. The inclusion is divided into ordinary inclusion, rare earth inclusion, and heavy metal inclusion. The brightness value of the ordinary inclusion is lower than the first current brightness of the target sample, and the brightness value of the rare earth inclusion and heavy metal inclusion is higher than the first current brightness of the target sample.

[0010] Optionally, determining the distribution of the first inclusion on the surface of the target sample based on the first current brightness, the second current brightness, the first standard brightness, and the second standard brightness includes:

[0011] Based on the first current brightness, the second current brightness, the first standard brightness, and the second standard brightness, determine the mapping relationship between the brightness value and the standard brightness value in the image information;

[0012] Based on the mapping relationship and the brightness value distribution information, the distribution of the first inclusion on the surface of the target sample is determined.

[0013] Optionally, the inclusion analysis method based on steel materials further includes:

[0014] Obtain the relative position of the standard analyte and the target sample;

[0015] When the standard test object is located on the surface of the target sample, the thickness information of the standard test object is obtained;

[0016] Based on the thickness information, the brightness correction area of ​​the image information is determined;

[0017] Based on the brightness correction area and the distribution of the first inclusion, the distribution of the second inclusion on the surface of the target sample is determined.

[0018] Optionally, before the step of acquiring image information of the target sample and the standard test substance, the method further includes:

[0019] Obtain a depth image of the surface of the target sample;

[0020] Based on the depth image, the target polishing thickness of the target sample is determined;

[0021] The surface of the target sample is polished according to the target polishing thickness.

[0022] Optionally, before the step of acquiring image information of the target sample and the standard test substance, the method further includes:

[0023] Obtain the current activation time of the light source in the environment where the target sample and the target test object are located;

[0024] Keep the light source on until the current activation time equals the target light source activation time.

[0025] Optionally, before the step of acquiring image information of the target sample and the standard test substance, the method further includes:

[0026] Adjust the pressure of the environment in which the target sample and the target test object are located to be less than a preset pressure threshold.

[0027] Optionally, acquiring image information of the target sample and the standard test substance includes:

[0028] Image information of the target sample and the standard test substance is acquired by backscattering.

[0029] Secondly, the present invention also provides an inclusion analysis device based on steel materials, comprising:

[0030] An image acquisition module is used to acquire image information of a target sample and a standard test substance, wherein the standard test substance is set within a preset range of the target sample, and the image information includes brightness value distribution information in the image;

[0031] A brightness acquisition module is used to acquire a first standard brightness of the target sample and a second standard brightness of the standard test object, wherein the first standard brightness is the brightness value of the target sample surface obtained by placing the target sample in a standard brightness environment, and the second standard brightness is the brightness value of the standard test object surface obtained by placing the target sample in a standard brightness environment.

[0032] The first determining module is used to determine the first current brightness of the target sample in the image information and the second current brightness of the standard test object in the image information based on the brightness value distribution information;

[0033] The second determining module is used to determine the distribution of a first inclusion on the surface of the target sample based on the first current brightness, the second current brightness, the first standard brightness, and the second standard brightness, wherein the distribution of the first inclusion includes the type of inclusion and its relative position in the target sample.

[0034] Thirdly, the present invention also provides an electronic device, including a memory and a processor, wherein the processor is used to execute a computer program stored in the memory to implement the steps of the inclusion analysis method based on steel materials as described in any of the first aspects above.

[0035] Fourthly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the inclusion analysis method based on steel materials as described in any of the first aspects above.

[0036] As can be seen from the above technical solutions, this application provides a method and related equipment for inclusion analysis based on steel materials. The method includes: acquiring image information of a target sample and a standard test object, wherein the standard test object is set within a preset range of the target sample, and the image information includes brightness value distribution information in the image; acquiring a first standard brightness of the target sample and a second standard brightness of the standard test object, wherein the first standard brightness is the brightness value of the target sample surface obtained by placing the target sample in a standard brightness environment, and the second standard brightness is the brightness value of the standard test object surface obtained by placing the target sample in a standard brightness environment; based on the brightness... The brightness distribution information determines the first current brightness of the target sample and the second current brightness of the standard test object in the image information. Based on the first current brightness, the second current brightness, the first standard brightness, and the second standard brightness, the distribution of a first inclusion on the surface of the target sample is determined. This first inclusion distribution includes the type of inclusion and its relative position within the target sample. The inclusions are classified as ordinary inclusions, rare earth inclusions, and heavy metal inclusions. The brightness value of ordinary inclusions is lower than the first current brightness of the target sample, while the brightness values ​​of rare earth and heavy metal inclusions are higher than the first current brightness of the target sample. This application embodiment acquires brightness information from images of the target sample and the standard test object. Based on this brightness information and the standard brightness of the target sample and the standard test object, a quantitative standard for brightness values ​​is established. This quantitative standard is then used to analyze and locate the inclusion distribution on the surface of the target sample. Since different materials have different colors and brightness values ​​in images, inclusion analysis based on brightness values ​​can determine the type and location of inclusions. By using the brightness information of the target sample and standard test material, a brightness quantification standard can be established under the current image acquisition environment, thereby more accurately determining the brightness distribution information on the surface of the target sample. Inclusions can be classified by their brightness values ​​and the first current brightness of the target sample, and the type of inclusion can be determined based on the classification. This can further improve the accuracy of inclusion analysis, thereby reducing the difficulty of analysis, saving analysis costs, improving the accuracy of analysis results, and increasing the efficiency of inclusion analysis. Attached Figure Description

[0037] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 A schematic flowchart illustrating a method for inclusion analysis of steel materials provided in this application embodiment;

[0039] Figure 2 A schematic structural diagram of an inclusion analysis device based on steel material provided in this application embodiment;

[0040] Figure 3 A schematic structural diagram of an electronic device provided in an embodiment of this application;

[0041] Figure 4 This is a schematic structural diagram of a computer-readable storage medium provided in an embodiment of this application. Detailed Implementation

[0042] The embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described below do not represent all embodiments consistent with this application. They are merely examples of systems and methods consistent with some aspects of this application as detailed in the claims. In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways, and the apparatus embodiments described below are merely exemplary.

[0043] like Figure 1 As shown, this application provides a method for inclusion analysis based on steel materials. The execution entity of this method can be a server or controller, etc., including:

[0044] Step S110: Obtain image information of the target sample and the standard test substance, wherein the standard test substance is set within a preset range of the target sample, and the image information includes brightness value distribution information in the image.

[0045] For example, the aforementioned standard test object can be a material with a brightness value significantly different from that of the target sample. The aforementioned preset range can be the edge of the target sample. For instance, when the aforementioned standard test object is aluminum foil, the edge of the aluminum foil can be aligned with the edge of the standard test object, and the aluminum foil can be attached to the surface of the target sample. The aforementioned brightness value distribution information can be obtained by acquiring color value information from the image information of the target sample and the standard test object, or by acquiring grayscale value information from the grayscale image of the target sample and the standard test object, wherein the aforementioned brightness value distribution information includes the distribution of pixels in the image and their corresponding color values ​​or grayscale values.

[0046] Step S120: Obtain the first standard brightness of the target sample and the second standard brightness of the standard test object, wherein the first standard brightness is the brightness value of the target sample surface obtained by placing the target sample in a standard brightness environment, and the second standard brightness is the brightness value of the standard test object surface obtained by placing the target sample in a standard brightness environment.

[0047] Step S130: Based on the above brightness value distribution information, determine the first current brightness of the target sample in the above image information and the second current brightness of the standard test object in the above image information.

[0048] For example, based on the distribution of brightness values ​​in the area excluding the standard test object on the surface of the target sample, the brightness value with the largest area proportion can be used as the first current brightness of the target sample. The first current brightness and the second current brightness can be determined based on the relative positional relationship between the target sample and the standard test object.

[0049] Step S140: Determine the distribution of the first inclusions on the surface of the target sample based on the first current brightness, the second current brightness, the first standard brightness, and the second standard brightness. The distribution of the first inclusions includes the type of inclusions and their relative positions in the target sample. The inclusions are classified into ordinary inclusions, rare earth inclusions, and heavy metal inclusions. The brightness value of the ordinary inclusions is lower than the first current brightness of the target sample, while the brightness value of the rare earth inclusions and heavy metal inclusions is higher than the first current brightness of the target sample.

[0050] For example, the inclusion brightness of a first inclusion on the surface of the target sample can be determined based on the first current brightness and the second current brightness. If the difference between the inclusion brightness and the first current brightness is higher than a preset brightness difference, the shape and location information of the inclusion can be determined based on the region associated with the inclusion brightness value. A brightness quantification standard for the current image information can be established based on the first current brightness, the second current brightness, the first standard brightness, and the second standard brightness. The inclusion brightness can be corrected based on the brightness quantification standard, and the type of inclusion can be determined based on the corrected brightness value.

[0051] Since different materials have different colors and brightness values ​​in images, inclusion analysis based on brightness values ​​can determine the type and location of inclusions. By using the brightness information of the target sample and standard test material, a brightness quantification standard can be established under the current image acquisition environment, thereby more accurately determining the brightness distribution information on the surface of the target sample. Inclusions can be classified by their brightness values ​​and the first current brightness of the target sample, and the type of inclusion can be determined based on the classification. This can further improve the accuracy of inclusion analysis, thereby reducing the difficulty of analysis, saving analysis costs, improving the accuracy of analysis results, and increasing the efficiency of inclusion analysis.

[0052] In one feasible implementation, determining the distribution of the first inclusion on the surface of the target sample based on the first current brightness, the second current brightness, the first standard brightness, and the second standard brightness includes:

[0053] Based on the first current brightness, the second current brightness, the first standard brightness, and the second standard brightness, the mapping relationship between the brightness value and the standard brightness value in the image information is determined.

[0054] Based on the above mapping relationship and the above brightness value distribution information, the distribution of the first inclusion on the surface of the target sample is determined.

[0055] For example, a direct proportional relationship can be established using the first brightness difference between the first current brightness and the second current brightness, and the second brightness difference between the first standard brightness and the second standard brightness. Based on this direct proportional relationship and the inclusion brightness value, the standard brightness value of the inclusion in a standard brightness environment can be determined. Alternatively, the influence curve of illumination on brightness can be established by combining the current light intensity of the image acquisition environment with the first and second brightness differences.

[0056] By determining the mapping relationship between the brightness values ​​in the image information and the standard brightness values, the brightness quantification evaluation system can be improved, the accuracy of the standard brightness values ​​of inclusions can be enhanced, and thus the accuracy of inclusion type analysis, the efficiency of inclusion analysis, and the objectivity of the results can be improved.

[0057] In one feasible implementation, the above-described inclusion analysis method based on steel materials further includes:

[0058] Obtain the relative positions of the aforementioned standard test substance and the aforementioned target sample;

[0059] When the aforementioned standard test object is located on the surface of the aforementioned target sample, the thickness information of the aforementioned standard test object is obtained;

[0060] Based on the thickness information mentioned above, the brightness correction area of ​​the image information is determined.

[0061] Based on the brightness correction area and the distribution of the first inclusion, the distribution of the second inclusion on the surface of the target sample is determined.

[0062] For example, when the standard test object is located on the surface of the target sample, the thickness information and relative position of the standard test object can be obtained. The shadow area formed by the standard test object on the surface of the target sample can be determined based on the thickness information and relative position. The shadow influence distribution in the shadow area can be determined based on the light source direction, light source intensity, thickness information of the standard test object, and shadow area in the current acquisition environment. The shadow influence distribution includes the value of the shadow's influence on the brightness value and its corresponding position.

[0063] By determining the brightness correction area of ​​the image information based on the thickness and relative position of the standard test object to the surface of the target sample, and correcting the image according to the brightness correction tendency, the influence of the shadow formed by the thickness of the standard test object on the surface of the target sample on the distribution of image brightness values ​​can be reduced. This can improve the brightness quantification evaluation system, improve the accuracy of the standard brightness values ​​of inclusions, thereby improving the accuracy of inclusion type analysis, the efficiency of inclusion analysis, and the objectivity of the results.

[0064] In one feasible implementation, prior to the step of acquiring image information of the target sample and the standard analyte described above, the method further includes:

[0065] Obtain a depth image of the surface of the target sample;

[0066] Based on the aforementioned depth image, the target grinding thickness of the target sample is determined.

[0067] The surface of the target sample is polished according to the target polishing thickness.

[0068] For example, the surface height difference of the target sample can be determined using the aforementioned depth image, and the target grinding thickness of the target sample can be determined based on this surface height difference. After grinding, the surface of the target sample can be cleaned to remove particles generated during grinding. The surface of the target sample can be ground and polished using materials such as silicon carbide or diamond to avoid introducing other metal inclusions.

[0069] The inconsistent thickness of the target sample surface can lead to a large difference in brightness values ​​between the recessed and protruding areas of the same material, thus affecting the accuracy of brightness value distribution information and consequently the determination of inclusion brightness values. Grinding the surface of the target sample can standardize the collection of brightness values, improve the brightness quantification evaluation system, and enhance the accuracy of inclusion standard brightness values. This, in turn, can improve the accuracy of inclusion type analysis, increase the efficiency of inclusion analysis, and enhance the objectivity of the results.

[0070] In one feasible implementation, prior to the step of acquiring image information of the target sample and the standard analyte described above, the method further includes:

[0071] Obtain the current activation time of the light source in the environment where the target sample and the target test object are located;

[0072] Keep the above light source on until the current activation time equals the target light source activation time.

[0073] For example, the start-up time of the aforementioned target light source can be 1-3 hours.

[0074] By adjusting the current activation time of the light source in the environment where the target object is located, we can avoid the high brightness instability caused by the light source being on for too short a time, and also avoid the energy waste and light source wear caused by the light source being on for too long a time. This can save analysis costs, improve the brightness quantification evaluation system, and improve the accuracy of the standard brightness value of inclusions. In this way, we can improve the accuracy of inclusion type analysis, improve the efficiency of inclusion analysis and the objectivity of the results.

[0075] In one feasible implementation, prior to the step of acquiring image information of the target sample and the standard analyte described above, the method further includes:

[0076] Adjust the pressure of the environment in which the target sample and the target test object are located to be lower than the preset pressure threshold.

[0077] For example, the preset pressure threshold is 10 Pa.

[0078] Under high pressure conditions in the image acquisition environment, gas molecules may collide with high-speed electrons generated during image acquisition, leading to reduced electron beam stability and affecting the quality of image acquisition. Furthermore, due to the long operating time of the light source, residual oxygen in the environment can exacerbate filament oxidation, affecting the light source's lifespan. Therefore, reducing the pressure of the environment surrounding the target object and applying a vacuum treatment can improve image acquisition quality, extend the lifespan of the light source, reduce equipment wear and tear, and ultimately improve the economy and practicality of inclusion analysis methods.

[0079] In one feasible implementation, acquiring the image information of the target sample and the standard test substance includes:

[0080] Image information of the target sample and the standard test material was obtained by backscattering.

[0081] In backscattered electron diffraction, the electron yield increases with the atomic number of the element. Therefore, using backscattered electrons as an imaging signal can not only analyze morphological features, but also display atomic number contrast and perform compositional analysis on inclusions based on atomic numbers. This can further improve the intelligence of inclusion analysis, reduce the difficulty of analysis, save analysis time, and thus improve the practicality of inclusion analysis methods.

[0082] like Figure 2 As shown, Figure 2 A schematic structural diagram of an inclusion analysis device based on steel material provided in this application embodiment, the device comprising:

[0083] Image acquisition module 201 is used to acquire image information of target sample and standard test substance, wherein the standard test substance is set within a preset range of the target sample, and the image information includes brightness value distribution information in the image;

[0084] The brightness acquisition module 202 is used to acquire the first standard brightness of the target sample and the second standard brightness of the standard test object, wherein the first standard brightness is the brightness value of the target sample surface obtained by placing the target sample in a standard brightness environment, and the second standard brightness is the brightness value of the standard test object surface obtained by placing the target sample in a standard brightness environment.

[0085] The first determining module 203 is used to determine the first current brightness of the target sample in the image information and the second current brightness of the standard test object in the image information based on the brightness value distribution information.

[0086] The second determining module 204 is used to determine the distribution of the first inclusions on the surface of the target sample based on the first current brightness, the second current brightness, the first standard brightness, and the second standard brightness. The distribution of the first inclusions includes the type of inclusions and their relative positions in the target sample. The inclusions are classified into ordinary inclusions, rare earth inclusions, and heavy metal inclusions. The brightness value of the ordinary inclusions is lower than the first current brightness of the target sample, while the brightness value of the rare earth inclusions and heavy metal inclusions is higher than the first current brightness of the target sample.

[0087] An inclusion analysis device 200 based on steel materials can achieve Figure 1 The various processes implemented in the method embodiments are not described in detail here to avoid repetition.

[0088] Please see Figure 3 , Figure 3 This is a schematic structural diagram of an electronic device provided in an embodiment of this application.

[0089] This application provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor 320. When the processor 320 executes the computer program 311, it performs the following steps:

[0090] Image information of the target sample and the standard test substance is acquired, wherein the standard test substance is set within a preset range of the target sample, and the image information includes brightness value distribution information in the image;

[0091] The first standard brightness of the target sample and the second standard brightness of the standard test object are obtained, wherein the first standard brightness is the brightness value of the target sample surface obtained by placing the target sample in a standard brightness environment, and the second standard brightness is the brightness value of the standard test object surface obtained by placing the target sample in a standard brightness environment.

[0092] Based on the above brightness value distribution information, the first current brightness of the target sample in the above image information and the second current brightness of the standard test object in the above image information are determined;

[0093] Based on the first current brightness, the second current brightness, the first standard brightness, and the second standard brightness, the distribution of the first inclusions on the surface of the target sample is determined. The distribution of the first inclusions includes the type of inclusions and their relative positions in the target sample. The inclusions are classified into ordinary inclusions, rare earth inclusions, and heavy metal inclusions. The brightness value of the ordinary inclusions is lower than the first current brightness of the target sample, while the brightness value of the rare earth inclusions and heavy metal inclusions is higher than the first current brightness of the target sample.

[0094] In practical implementation, when the processor 320 executes the computer program 311, it can achieve... Figure 1 Any of the corresponding implementation methods in the embodiments.

[0095] Since the electronic device described in this embodiment is a device used to implement a device in the embodiments of this application, those skilled in the art can understand the specific implementation method and various variations of the electronic device in this embodiment based on the method described in the embodiments of this application. Therefore, how the electronic device implements the method in the embodiments of this application will not be described in detail here. Any device used by those skilled in the art to implement the method in the embodiments of this application falls within the scope of protection of this application.

[0096] like Figure 4 As shown, Figure 4 This is a schematic structural diagram of a computer-readable storage medium provided in an embodiment of this application.

[0097] This embodiment provides a computer-readable storage medium 400 on which a computer program 411 is stored. When the computer program 411 is executed by a processor, it performs the following steps:

[0098] Image information of the target sample and the standard test substance is acquired, wherein the standard test substance is set within a preset range of the target sample, and the image information includes brightness value distribution information in the image;

[0099] The first standard brightness of the target sample and the second standard brightness of the standard test object are obtained, wherein the first standard brightness is the brightness value of the target sample surface obtained by placing the target sample in a standard brightness environment, and the second standard brightness is the brightness value of the standard test object surface obtained by placing the target sample in a standard brightness environment.

[0100] Based on the above brightness value distribution information, the first current brightness of the target sample in the above image information and the second current brightness of the standard test object in the above image information are determined;

[0101] Based on the first current brightness, the second current brightness, the first standard brightness, and the second standard brightness, the distribution of the first inclusions on the surface of the target sample is determined. The distribution of the first inclusions includes the type of inclusions and their relative positions in the target sample. The inclusions are classified into ordinary inclusions, rare earth inclusions, and heavy metal inclusions. The brightness value of the ordinary inclusions is lower than the first current brightness of the target sample, while the brightness value of the rare earth inclusions and heavy metal inclusions is higher than the first current brightness of the target sample.

[0102] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0103] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0104] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0105] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0106] This application also provides a computer program product, which includes computer software instructions that, when executed on a processing device, cause the processing device to perform actions such as... Figure 1 The flowchart of the inclusion analysis method based on steel material in the corresponding embodiment.

[0107] The aforementioned computer program product includes one or more computer instructions. When the aforementioned computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The aforementioned computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The aforementioned computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the aforementioned computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The aforementioned computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The aforementioned available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state disks (SSDs)).

[0108] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0109] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units through some interfaces, and may be electrical, mechanical, or other forms.

[0110] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0111] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0112] If the aforementioned integrated units are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0113] In summary, the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for inclusion analysis based on steel materials, characterized in that, include: Image information of a target sample and a standard analyte is acquired, wherein the standard analyte is set within a preset range of the target sample, and the image information includes brightness value distribution information in the image; A first standard brightness of the target sample and a second standard brightness of the standard test object are obtained, wherein the first standard brightness is the brightness value of the target sample surface obtained by placing the target sample in a standard brightness environment, and the second standard brightness is the brightness value of the standard test object surface obtained by placing the target sample in a standard brightness environment. Based on the brightness value distribution information, determine the first current brightness of the target sample in the image information and the second current brightness of the standard test object in the image information; Based on the first current brightness, the second current brightness, the first standard brightness, and the second standard brightness, the distribution of the first inclusion on the surface of the target sample is determined. The distribution of the first inclusion includes the type of inclusion and its relative position in the target sample. The inclusion is divided into ordinary inclusions, rare earth inclusions, and heavy metal inclusions. The brightness value of the ordinary inclusion is lower than the first current brightness of the target sample, and the brightness value of the rare earth inclusions and heavy metal inclusions is higher than the first current brightness of the target sample. Obtain the relative position of the standard analyte and the target sample; When the standard test object is located on the surface of the target sample, the thickness information of the standard test object is obtained; Based on the thickness information, the brightness correction area of ​​the image information is determined; Based on the brightness correction area and the distribution of the first inclusion, the distribution of the second inclusion on the surface of the target sample is determined; The area of ​​the shadow cast by the standard test object on the surface of the target sample is determined based on the thickness information and relative position of the standard test object. Based on the light source direction, light source intensity, thickness information of the standard test object, and shadow area in the current acquisition environment, the distribution of shadow influence in the shadow area is determined, wherein the distribution of shadow influence includes the numerical value of the shadow's influence on the brightness value and its corresponding location; Prior to the step of acquiring image information of the target sample and the standard test substance, the method further includes: Adjust the pressure of the environment in which the target sample and the standard test object are located to be less than a preset pressure threshold.

2. The inclusion analysis method based on steel materials as described in claim 1, characterized in that, The step of determining the distribution of the first inclusion on the surface of the target sample based on the first current brightness, the second current brightness, the first standard brightness, and the second standard brightness includes: Based on the first current brightness, the second current brightness, the first standard brightness, and the second standard brightness, determine the mapping relationship between the brightness value and the standard brightness value in the image information; Based on the mapping relationship and the brightness value distribution information, the distribution of the first inclusion on the surface of the target sample is determined.

3. The inclusion analysis method based on steel materials as described in claim 1, characterized in that, Prior to the step of acquiring image information of the target sample and the standard test substance, the method further includes: Obtain a depth image of the surface of the target sample; Based on the depth image, the target polishing thickness of the target sample is determined; The surface of the target sample is polished according to the target polishing thickness.

4. The inclusion analysis method based on steel materials as described in claim 1, characterized in that, Prior to the step of acquiring image information of the target sample and the standard test substance, the method further includes: Obtain the current activation time of the light source in the environment where the target sample and the standard test substance are located; Keep the light source on until the current activation time equals the target light source activation time.

5. The inclusion analysis method based on steel materials as described in claim 3, characterized in that, The acquisition of image information of the target sample and standard test material includes: Image information of the target sample and the standard test substance is acquired by backscattering.

6. An inclusion analysis device based on steel materials, characterized in that, For performing the inclusion analysis method based on ferrous materials as described in any one of claims 1 to 5, the inclusion analysis apparatus based on ferrous materials comprises: An image acquisition module is used to acquire image information of a target sample and a standard test substance, wherein the standard test substance is set within a preset range of the target sample, and the image information includes brightness value distribution information in the image; A brightness acquisition module is used to acquire a first standard brightness of the target sample and a second standard brightness of the standard test object, wherein the first standard brightness is the brightness value of the target sample surface obtained by placing the target sample in a standard brightness environment, and the second standard brightness is the brightness value of the standard test object surface obtained by placing the target sample in a standard brightness environment. The first determining module is used to determine the first current brightness of the target sample in the image information and the second current brightness of the standard test object in the image information based on the brightness value distribution information; The second determining module is used to determine the distribution of a first inclusion on the surface of the target sample based on the first current brightness, the second current brightness, the first standard brightness, and the second standard brightness. The first inclusion distribution includes the type of inclusion and its relative position in the target sample. The inclusion is divided into ordinary inclusions, rare earth inclusions, and heavy metal inclusions. The brightness value of the ordinary inclusions is lower than the first current brightness of the target sample, and the brightness value of the rare earth inclusions and heavy metal inclusions is higher than the first current brightness of the target sample.

7. An electronic device, comprising a memory and a processor, characterized in that, When the processor is used to execute the computer program stored in the memory, it implements the steps of the inclusion analysis method based on steel materials as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the steps of the inclusion analysis method based on steel materials as described in any one of claims 1 to 5.

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