Quantitative evaluation method for black ash on strip steel surface and related equipment

Abstract

This application provides a method and related equipment for quantitative evaluation of black and gray areas on the surface of steel strips. The method includes: acquiring physical samples of black and gray areas on the surface of steel strips; generating a black and gray area distribution image on the surface of steel strips based on the physical samples; segmenting the black and gray area distribution image into multiple regions; and obtaining a quantitative evaluation of the black and gray areas on the surface of steel strips based on the grayscale value of each region. Thus, by acquiring physical samples of black and gray areas on the surface of steel strips, generating a black and gray area distribution image based on the samples, and obtaining the image grayscale value, a quantitative evaluation of black and gray areas in any region of the steel strip surface can be achieved.

Description

Technical Field

[0001] This invention relates to the field of steel rolling technology, and in particular to a quantitative evaluation method and related equipment for black ash on the surface of strip steel. Background Technology

[0002] Black ash on hot-rolled strip steel, mainly manifested as fine black powdery iron oxide scale distributed on the surface of the steel plate, is a type of iron oxide scale defect in hot-rolled steel. This defect not only directly affects the product's appearance but also has a significant adverse impact on downstream users' processing and coating processes, potentially leading to product scrapping and increased quality losses. Furthermore, this defect generates a large amount of dust during steel plate processing, posing a threat to the environment and human health.

[0003] In existing technologies, the main methods for evaluating black ash on the surface of steel strips are visual inspection and weighing. Visual inspection is heavily influenced by the observer's subjectivity, resulting in low accuracy and limiting its application to qualitative evaluation of black ash. Weighing, on the other hand, is significantly affected by the accuracy of the weighing instrument, typically requiring the collection of black ash over a large area to reach the instrument's minimum detection weight, thus failing to evaluate black ash in localized areas. Summary of the Invention

[0004] This invention provides a quantitative evaluation method for black ash on the surface of steel strip, which solves the problems that when using manual methods to determine black ash on the surface of steel strip, the subjective factors are too great and only qualitative evaluation can be performed; while the results of the weighing method are greatly affected by the accuracy of the weighing instrument and cannot achieve evaluation of the local black ash state.

[0005] In a first aspect, the present invention provides a method for quantitatively evaluating black ash on the surface of steel strip, comprising:

[0006] Obtain solid samples of black and gray material from the surface of the steel strip;

[0007] Based on the black and gray solid sample, generate a black and gray distribution image on the surface of the strip steel;

[0008] The black and gray distribution image is segmented into multiple regions, and a quantitative evaluation of the black and gray on the strip surface is obtained based on the gray value of each region.

[0009] Optionally, the black and gray solid sample on the strip surface is a sample of the original black and gray distribution state of the strip surface obtained by contacting the steel plate surface with a transparent adhesive.

[0010] Optionally, generating a black and gray distribution image of the strip surface based on the black and gray entity sample includes:

[0011] The image acquisition device is controlled to acquire images of the black and gray physical sample under a preset reference background, generating a black and gray distribution image of the strip surface, wherein the gray level of the preset reference background is greater than the maximum gray level of the black and gray physical sample.

[0012] Optionally, the step of segmenting the black-gray distribution image into multiple regions and obtaining a quantitative evaluation of the black-gray on the strip surface based on the gray value of each region includes:

[0013] The black and gray distribution image is divided into multiple regions, and the relative gray level of each region is determined based on the gray level value of each region and the maximum gray level value among all regions.

[0014] A quantitative evaluation of the black and gray color on the strip surface is obtained based on the relative grayness of each region.

[0015] Optionally, determining the relative gray level of each region based on the gray level value of each region and the maximum gray level value among all regions includes:

[0016] Through formula g ij =G ij / G max The relative gray level g of each region is obtained. ij ,

[0017] Among them, G ij G represents the grayscale value of the region in the i-th row and j-th column. max This represents the maximum grayscale value among all grayscale values ​​in the region.

[0018] Optionally, the quantitative evaluation of the black and gray on the strip surface based on the relative gray level of each region includes:

[0019] Using formula Obtain the quantitative evaluation value l of the black ash on the strip surface.

[0020] Wherein, m is the total number of rows in the segmented region of the black and gray distribution image on the strip surface, and n is the total number of columns in the segmented region of the black and gray distribution image on the strip surface.

[0021] Optionally, the black-and-gray distribution image is segmented into multiple regions, and the relative gray level of each region is determined based on the gray level value of each region and the maximum gray level value among all regions. This is characterized by including:

[0022] The image acquisition device is controlled to acquire images of the black and gray entity sample under a preset reference background, and an image of the preset reference background that does not cover the black and gray entity sample is generated.

[0023] The reference grayscale value of the image of the preset reference background is obtained based on the image of the preset reference background;

[0024] Based on the grayscale value of each region and the reference grayscale value, the maximum grayscale value among all the grayscale values ​​of the regions is determined.

[0025] Optionally, based on the grayscale value of each of the regions and the reference grayscale value, determining the maximum grayscale value among all the grayscale values ​​of the regions includes:

[0026] pass The maximum gray value G among all the gray values ​​of the regions is obtained. max Where Ga is the reference grayscale value, and Gb is the maximum grayscale value in each region.

[0027] Secondly, the present invention also provides a quantitative evaluation device for black ash on the surface of steel strip, comprising:

[0028] The acquisition module is used to acquire black and gray solid samples from the surface of the steel strip.

[0029] The control module is used to generate a black and gray distribution image on the surface of the strip steel based on the black and gray entity sample.

[0030] The image processing module is used to segment the black and gray distribution image into multiple regions and obtain a quantitative evaluation of the black and gray on the strip surface based on the gray value of each region.

[0031] 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 quantitative evaluation method for black ash on the surface of strip steel as described in any of the first aspects above.

[0032] Fourthly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the quantitative evaluation method for black ash on the surface of strip steel as described in any of the first aspects above.

[0033] As can be seen from the above technical solutions, this application provides a method and related equipment for quantitative evaluation of black ash on the surface of steel strip. The method includes: acquiring physical samples of black ash on the surface of steel strip; generating a black ash distribution image on the surface of steel strip based on the physical samples; dividing the black ash distribution image into multiple regions; and obtaining a quantitative evaluation of the black ash on the surface of steel strip based on the gray value of each region. Since the human observation method evaluates the black ash by observing the surface of the steel plate, this method is greatly affected by the observer's subjective factors and cannot achieve a quantitative evaluation of the black ash, only a qualitative evaluation. The weighing method collects black ash from the surface of steel strip and weighs it using a weighing instrument to achieve a quantitative evaluation of the black ash on the surface of steel strip. However, since black ash is lightweight, it is greatly affected by the accuracy of the instrument, and only a large amount of black ash can be weighed at once, making it impossible to achieve a quantitative evaluation of black ash in any region. This application, however, acquires physical samples of black ash on the surface of steel strip, generates a black ash distribution image based on the samples, and performs a quantitative evaluation of the black ash on the surface of steel strip based on the image gray value. This invention avoids the subjective factors inherent in human observation methods and solves the problem that human observation methods cannot quantitatively evaluate the black and gray areas on the strip surface. The embodiments of this application segment the generated black and gray image of the strip surface into multiple regions, and quantitatively evaluate the black and gray areas on the strip surface based on the grayscale value of each region. This solves the problem that the weighing method cannot quantitatively evaluate the black and gray areas of any region on the strip surface, thus achieving quantitative evaluation of the black and gray areas of any region on the strip surface. Attached Figure Description

[0034] 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.

[0035] Figure 1 A schematic flowchart illustrating a method for quantitatively evaluating black ash on the surface of steel strip, provided for embodiments of this application;

[0036] Figure 2 An image showing the distribution of black and gray on the surface of a steel strip, provided as an embodiment of this application;

[0037] Figure 3 The grayscale values ​​G of different regions on a black-gray distribution image of a strip surface provided in this application embodiment are shown. ij Data distribution;

[0038] Figure 4 The relative gray levels g of different regions on a black-gray distribution image of a strip surface provided in this application embodiment are shown. ij Data distribution;

[0039] Figure 5An image showing the distribution of black and gray on the surface of a steel strip, provided as an embodiment of this application;

[0040] Figure 6 The relative gray levels g of different regions on a black-gray distribution image of a strip surface provided in this application embodiment are shown. ij Data distribution;

[0041] Figure 7 A schematic structural diagram of a quantitative evaluation device for black ash on the surface of steel strip provided by the present invention;

[0042] Figure 8 A schematic diagram illustrating an embodiment of an electronic device provided by the present invention;

[0043] Figure 9 This is a schematic diagram of an embodiment of a computer-readable storage medium provided by the present invention. Detailed Implementation

[0044] 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.

[0045] The quantitative evaluation method for black ash on the surface of steel strip provided in this application embodiment, such as Figure 1 As shown. The entities executing the above method may include a controller for a quantitative evaluation device for black ash on the surface of strip steel, factory workers, and a server in the factory with a built-in pricing evaluation program for black ash on the surface of strip steel. The above quantitative evaluation method for black ash on the surface of strip steel includes:

[0046] Step S110: Obtain a black and gray solid sample from the surface of the strip steel.

[0047] Optionally, the above-mentioned black and gray solid samples on the strip surface are samples of the original black and gray distribution state of the strip surface obtained by contacting the steel plate surface with a transparent adhesive.

[0048] For example, a controller can be used to control a mechanical device loaded with a transparent adhesive to obtain a sample of the original black and gray distribution state of the strip surface by contacting the steel plate surface; or factory workers can directly use the transparent adhesive to pick up a sample of the black and gray solid from the steel plate surface.

[0049] The original black and gray distribution state of the steel strip surface obtained by contacting the steel plate surface with a transparent adhesive can completely preserve the original distribution of black and gray on the steel plate surface, so that the gray value measurement results of each area are more consistent with the area and closer to the true black and gray distribution state.

[0050] Step S120: Based on the black and gray entity samples obtained above, generate a black and gray distribution image on the surface of the strip steel.

[0051] Optionally, generating a black and gray distribution image of the strip surface based on the aforementioned black and gray entity sample includes:

[0052] The image acquisition device is controlled to acquire images of the black and gray physical sample under a preset reference background, generating a black and gray distribution image of the strip surface, wherein the gray level of the preset reference background is greater than the maximum gray level of the black and gray physical sample.

[0053] For example, the mechanical device loaded with the transparent adhesive can be controlled by a controller to fix the black and gray solid sample onto a preset reference background, and then the image acquisition device can be controlled to acquire an image of the black and gray solid sample to generate an image of the black and gray distribution on the steel strip surface; alternatively, factory workers can fix the transparent adhesive onto the preset reference background and directly photograph the black and gray solid sample. The grayscale of the preset reference background is greater than the maximum grayscale of the black and gray solid sample.

[0054] By collecting the grayscale value of a preset reference background and comparing it with the maximum grayscale value among all areas of the black and gray strip surface, the grayscale values ​​of all areas can be corrected, eliminating the influence of factors such as exposure during image acquisition on the overall image grayscale value, and improving the accuracy and scientific nature of the results.

[0055] Step S130: Divide the above black and gray distribution image into multiple regions, and obtain a quantitative evaluation of the black and gray on the strip surface based on the gray value of each region.

[0056] Optionally, the above-mentioned black and gray distribution image is segmented into multiple regions, and a quantitative evaluation of the black and gray on the strip surface is obtained based on the gray value of each region, including:

[0057] The above black and gray distribution image is divided into multiple regions. Based on the gray value of each region and the maximum gray value among all regions, the relative gray value of each region is determined.

[0058] A quantitative evaluation of the black and gray color on the strip surface is obtained based on the relative grayness of each region.

[0059] For example, the image recognition device can be controlled by the controller to process the above-mentioned black and gray distribution image; the image can be processed by the built-in image recognition algorithm of the factory server, dividing the image into multiple continuous regions, obtaining the average gray value of each region as the gray value of each region, determining the relative gray value of each region based on the gray value of each region and the maximum gray value among all regions; and obtaining a quantitative evaluation of the black and gray on the strip surface based on the relative gray value of each region.

[0060] Optionally, based on the grayscale value of each region and the maximum grayscale value among all regions, the relative grayscale of each region is determined, including:

[0061] Through formula g ij =G ij / G max The relative gray level g of each region is obtained. ij .

[0062] Among them, G ij G represents the grayscale value of the region in the i-th row and j-th column. max This represents the maximum grayscale value among all grayscale values ​​in the region.

[0063] By determining the relative gray level of each region based on its gray level and the maximum gray level among all regions, the deviation between the gray level of each region and the ideal gray level can be corrected due to differences in exposure and the presence of dust on the steel plate surface, thereby improving the scientific validity and accuracy of the results.

[0064] It should be noted that the grayscale value of the image ranges from [0, 255]. The larger the grayscale value, the whiter the image; the smaller the grayscale value, the darker the image.

[0065] Optionally, the above black-and-gray distribution image is segmented into multiple regions, and the relative gray level of each region is determined based on the gray level value of each region and the maximum gray level value among all regions, including:

[0066] The image acquisition device is controlled to acquire images of black and gray physical samples under a preset reference background, generating the aforementioned black and gray distribution image on the steel strip surface and an image of the preset reference background that does not cover the black and gray physical samples.

[0067] Based on the image of the preset reference background, the grayscale value of the image of the preset reference background is obtained and used as the reference grayscale value.

[0068] Based on the grayscale value and reference grayscale value of each region, determine the maximum grayscale value among all regions.

[0069] Furthermore, adding a reference grayscale value as a control can eliminate the situation where the grayscale value of each area is lower than the ideal state due to different exposure levels during image acquisition, thereby improving the scientific nature and accuracy of the results.

[0070] Optionally, based on the grayscale value of each region and a reference grayscale value, determine the maximum grayscale value among all regions, including:

[0071] pass Find the maximum gray value G among all gray values ​​in the region. max .

[0072] Among them, G a For reference grayscale values, G b The maximum grayscale value for each region.

[0073] It should be noted that the above formula calculates the maximum gray value G among all gray values ​​in all regions. max This method can correct the deviation between the actual measured reference grayscale value and the ideal reference grayscale value caused by factors such as exposure when the image acquisition device acquires black and gray entity samples. It aims to minimize the impact of exposure on the grayscale value G of each region. ij The impact of this on improving the scientific rigor and accuracy of the evaluation results. This leads to G max With G a Other possible reasons for the inequality include: when using a transparent adhesive to obtain a sample of the original black and gray distribution on the steel strip surface, there may be dust or other substances on the steel plate surface that affect the image grayscale value, resulting in the grayscale value of the area not covered by black and gray being unequal to the reference grayscale value.

[0074] Optionally, a quantitative evaluation of the black and gray color on the strip surface is obtained based on the relative gray level of each region, including:

[0075] Using formula Obtain the quantitative evaluation value l of the black ash on the strip surface.

[0076] Where m is the total number of rows in the black and gray distribution image of the strip surface divided into regions, and n is the total number of columns in the black and gray distribution image of the strip surface divided into regions.

[0077] By calculating the quantitative evaluation value l of black ash on the surface of the strip steel, the distribution state of black ash on the surface of the strip steel can be quantified, which facilitates the comparison of black ash distribution between different strip steels and between different areas of the same strip steel, thereby improving the scientificity and practicality of the evaluation results.

[0078] The invention is further illustrated by taking the quantitative evaluation of surface black and gray residue on a steel strip with a slight black and gray appearance as an example. For example... Figure 1As shown, the quantitative evaluation method for black ash on the surface of steel strip provided by the present invention includes the following steps:

[0079] S110. Obtain a solid black and gray sample from the surface of the steel strip.

[0080] For example, transparent tape is applied to the surface of a steel plate, and black ash adheres to the surface of the steel plate.

[0081] S120. Based on the above black and gray entity samples, generate a black and gray distribution image on the surface of the strip steel.

[0082] For example, transparent tape with black ash adhering to it is fixed onto ordinary white A4 paper, and an image is captured using a camera to obtain an image of the black ash distribution on the steel strip surface, as shown below. Figure 2 As shown.

[0083] S130. Divide the above black and gray distribution image into multiple regions, and obtain a quantitative evaluation of the black and gray on the strip surface based on the gray value of each region.

[0084] For example, the black-and-gray distribution image is divided horizontally into 50 rows and vertically into 50 columns, resulting in a total of 2500 continuous regions. Using an image recognition algorithm, the grayscale value G of each region is obtained. ij Data distribution as follows Figure 3 As shown.

[0085] Figure 3 According to the embodiments of this application Figure 2 This provides a black and gray distribution image of a steel strip surface, showing the gray values ​​G of different regions on the steel strip surface. ij Data distribution. This includes data based on the grayscale values ​​G of different regions. ij Draw a frequency distribution histogram and quantile table for the discrete random variable. It should be noted that in the frequency distribution histogram, the width of each rectangle represents the class interval of the sample group, and the length of each rectangle represents the sample frequency, reflecting the frequency distribution pattern of the sample. In the quantile table, the percentile is a set of n observations arranged in ascending order; the value at the p% position is called the p-th percentile. Therefore, Figure 3 The value corresponding to the median 100.0% is the maximum gray value G among all gray values ​​in the region. max ,therefore, Figure 2 A G corresponding to a black and gray distribution image on the surface of a steel strip is provided. max It is 156.52.

[0086] Using formula g ij =G ij / G max ,according to Figure 2 This provides a black and gray distribution image of a steel strip surface, from which the relative gray level of each region is obtained. The data distribution is as follows: Figure 4As shown.

[0087] Using formula The quantitative evaluation value 'l' of the black ash on the surface of the steel strip was obtained. Among them, The meaning is relative gray level g ij The average value.

[0088] Figure 4 According to the embodiments of this application Figure 2 This provides a black and gray distribution image of a steel strip surface, showing the relative gray levels g of different regions on the steel strip surface. ij The data distribution includes the relative gray levels g of different regions. ij The frequency distribution histogram, quantile table, and sample summary statistics table of the discrete random variable were plotted. Therefore, the relative gray level g can be derived. ij The average value is 0.90.

[0089] The quantitative evaluation value of black ash on the strip surface can be obtained by calculation: l = 100 × 0.90 = 90.

[0090] The present invention is further illustrated by taking the quantitative evaluation of surface black ash on a steel strip with severe surface black ash as an example.

[0091] S110. Obtain a solid black and gray sample from the surface of the steel strip.

[0092] For example, transparent tape is applied to the surface of a steel plate, and black ash adheres to the surface of the steel plate.

[0093] S120. Based on the above black and gray entity samples, generate a black and gray distribution image on the surface of the strip steel.

[0094] For example, transparent tape with black ash adhering to it is fixed onto ordinary white A4 paper, and an image is captured using a camera to obtain an image of the black ash distribution on the steel strip surface, as shown below. Figure 5 As shown.

[0095] S130. Divide the above black and gray distribution image into multiple regions, and obtain a quantitative evaluation of the black and gray on the strip surface based on the gray value of each region.

[0096] For example, the black-and-gray distribution image is divided horizontally into 50 rows and vertically into 50 columns, resulting in a total of 2500 continuous regions. Using an image recognition algorithm, the grayscale value G of each region is obtained. ij Using formula g ij =G ij / G max The relative gray level of each region is obtained, and the data distribution is as follows: Figure 6 As shown.

[0097] Using formula The quantitative evaluation value 'l' of the black ash on the surface of the steel strip was obtained. Among them, The meaning is relative gray level g ij The average value.

[0098] Figure 6 According to the embodiments of this application Figure 5 This provides a black and gray distribution image of a steel strip surface, showing the relative gray levels g of different regions on the steel strip surface. ij The data distribution includes the relative gray levels g of different regions. ij The frequency distribution histogram, quantile table, and sample summary statistics table for the discrete random variable were plotted. Therefore, it can be seen that the relative gray level g... ij The average value is 0.54.

[0099] The quantitative evaluation value of black ash on the strip surface can be obtained by calculation: l = 100 × 0.54 = 54.

[0100] It should be noted that the visual inspection method for judging the black ash condition on the strip surface is highly susceptible to the subjective factors of the observer, resulting in low accuracy and only allowing for a qualitative evaluation of the black ash. The weighing method, on the other hand, is greatly affected by the accuracy of the weighing instrument, typically requiring the collection of black ash from a large area to reach the instrument's minimum detection weight, making it impossible to evaluate black ash in localized areas. Therefore, neither of these methods can provide a quantitative evaluation of black ash in localized areas of the strip surface.

[0101] In this application, by obtaining a black and gray solid sample from the surface of the strip steel, generating a black and gray distribution image based on the sample, obtaining the image gray value, and performing analysis based on the image gray value, the problem of the existing solution being unable to quantitatively evaluate the black and gray in any area of ​​the strip steel surface is solved.

[0102] As can be seen from the above technical solutions, the embodiments of the present invention provide a method for quantitative evaluation of black and gray areas on the surface of strip steel. This method involves obtaining physical samples of black and gray areas on the surface of strip steel; generating a black and gray distribution image on the surface of strip steel based on the physical samples; dividing the black and gray distribution image into multiple regions; and obtaining a quantitative evaluation of the black and gray areas on the surface of strip steel based on the grayscale value of each region. Thus, by obtaining physical samples of black and gray areas on the surface of strip steel, generating a black and gray distribution image based on the samples, and obtaining the image grayscale value, a quantitative evaluation of black and gray areas in any region of the strip steel surface can be achieved.

[0103] Please see Figure 7 , Figure 7 This is a schematic structural diagram of a quantitative evaluation device for black ash on the surface of steel strip provided by the present invention. Figure 7 As shown, a quantitative evaluation device 700 for black ash on the surface of steel strip includes a data acquisition module 701, a control module 702, and an image processing module 703, wherein:

[0104] Acquisition module 701 is used to acquire black and gray solid samples from the surface of the strip steel;

[0105] Control module 702 is used to generate a black and gray distribution image on the surface of the strip steel based on the above-mentioned black and gray entity sample;

[0106] The image processing module 703 is used to segment the above black and gray distribution image into multiple regions and obtain a quantitative evaluation of the black and gray on the strip surface based on the gray value of each region.

[0107] A quantitative evaluation device 700 for black ash on the surface of steel strip can achieve Figure 1 The various processes implemented by the device in the method embodiment will not be described again here to avoid repetition. Furthermore, a quantitative evaluation device 700 for black and gray areas on the surface of a strip steel can achieve quantitative evaluation of black and gray areas in any region of the strip steel surface by acquiring physical samples of black and gray areas on the strip steel surface, generating a black and gray distribution image based on the samples, and obtaining the image grayscale values.

[0108] Please see Figure 8 , Figure 8 This is a schematic structural diagram of an electronic device provided in an embodiment of this application.

[0109] like Figure 8 As shown, this application provides an electronic device 800, including a memory 810, a processor 820, and a computer program 811 stored in the memory 810 and executable on the processor 820. When the processor 820 executes the computer program 811, it performs the following steps:

[0110] Obtain solid samples of black and gray material from the surface of the steel strip;

[0111] Based on the above black and gray entity samples, a black and gray distribution image of the strip surface is generated;

[0112] The above black and gray distribution image is divided into multiple regions, and a quantitative evaluation of the black and gray on the strip surface is obtained based on the gray value of each region.

[0113] In practical implementation, when the processor 820 executes the computer program 811, it can achieve... Figure 1 Any of the corresponding implementation methods in the embodiments.

[0114] 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.

[0115] Please see Figure 9 , Figure 9 This is a schematic structural diagram of a computer-readable storage medium provided in an embodiment of this application.

[0116] like Figure 9 As shown, this embodiment provides a computer-readable storage medium 900 on which a computer program 911 is stored. When the computer program 911 is executed by a processor, it performs the following steps:

[0117] Obtain solid samples of black and gray material from the surface of the steel strip;

[0118] Based on the above black and gray entity samples, a black and gray distribution image of the strip surface is generated;

[0119] The above black and gray distribution image is divided into multiple regions, and a quantitative evaluation of the black and gray on the strip surface is obtained based on the gray value of each region.

[0120] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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 quantitative evaluation method for black ash on the surface of the strip steel in the corresponding embodiment.

[0126] The computer program product includes one or more computer instructions. When the 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 computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the 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 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 available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0127] 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.

[0128] 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 units 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 apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0129] The units described 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.

[0130] 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.

[0131] If the integrated unit is implemented as 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 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.

[0132] 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 quantitative evaluation method for black ash on the surface of steel strip, characterized in that, include: Obtain a solid sample of black and gray material on the surface of a strip steel, wherein the solid sample of black and gray material on the surface of the strip steel is a sample of the original black and gray distribution state of the strip steel surface obtained by contacting the surface of the steel plate with a transparent adhesive. Based on the black and gray solid sample, generate a black and gray distribution image on the surface of the strip steel; The black and gray distribution image is divided into multiple regions, and a quantitative evaluation of the black and gray on the strip surface is obtained based on the gray value of each region. The step of generating a black and gray distribution image of the strip surface based on the black and gray entity sample includes: The image acquisition device is controlled to acquire images of the black and gray physical sample under a preset reference background, generating a black and gray distribution image of the strip surface, wherein the gray level of the preset reference background is greater than the maximum gray level of the black and gray physical sample. The black-and-gray distribution image is segmented into multiple regions. Based on the grayscale value of each region and the maximum grayscale value among all regions, the relative grayscale value of each region is determined, whereby the formula g is used. ij =G ij / G max The relative gray level g of each region is obtained. ij Among them, G ij G represents the grayscale value of the region in the i-th row and j-th column. max The maximum grayscale value among all grayscale values ​​in all regions; The step of segmenting the black-gray distribution image into multiple regions and obtaining a quantitative evaluation of the black-gray on the strip surface based on the gray value of each region includes: Based on the relative gray level of each region, a quantitative evaluation of the black ash on the strip surface is obtained. The quantitative evaluation value of the black ash on the strip surface is obtained using a formula. Obtain a quantitative evaluation value of the black ash on the surface of the strip steel. Wherein, m is the total number of rows in the segmented region of the black and gray distribution image on the strip surface, and n is the total number of columns in the segmented region of the black and gray distribution image on the strip surface.

2. The method as described in claim 1, characterized in that, The black-and-gray distribution image is segmented into multiple regions. Based on the gray value of each region and the maximum gray value among all regions, the relative gray value of each region is determined, including: The image acquisition device is controlled to acquire images of the black and gray entity sample under a preset reference background, and an image of the preset reference background that does not cover the black and gray entity sample is generated. The reference grayscale value of the image of the preset reference background is obtained based on the image of the preset reference background; Based on the grayscale value of each region and the reference grayscale value, the maximum grayscale value among all the grayscale values ​​of the regions is determined.

3. An electronic device, comprising a memory and a processor, characterized in that, When the processor executes the computer program stored in the memory, it implements the steps of the quantitative evaluation method for black ash on the surface of strip steel as described in any one of claims 1 to 2.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the quantitative evaluation method for black ash on the surface of strip steel as described in any one of claims 1 to 2.

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