Method, device, and program for identifying type of plating of automobile steel plate

Abstract

To provide a method, device, and program for identifying a type of plating of an automobile steel plate for identifying a type of plating applied onto a steel plate to be used for a vehicle body configuration component of an automobile body.SOLUTION: A method for identifying a type of plating of an automobile body is a method for identifying a type of plating applied onto a steel plate to be used for a vehicle body configuration component of the automobile body. The method comprises: a steel plate cross-section gray scale image acquisition process S1 of sampling a steel plate from the vehicle body configuration component so as to manufacture a test piece including the steel plate, and imaging an optical microscopic photograph of the steel plate cross-section in the manufactured test piece so as to acquire a gray scale image; a gray scale gradation histogram generation process S3 of generating a histogram of a frequency of a gray scale gradation in the acquired gray scale image; and a plating type identification process S5 of identifying a type of plating applied onto the steel plate based on a distribution form of the generated histogram.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a method, an apparatus, and a program for identifying the type of plating applied to steel sheets for use in automobile body components. [Background technology]

[0002] The various types of steel sheets used as materials for the components that make up an automobile body have continued to change over the years, with progress being made in terms of strength, thinness and weight reduction. In particular, automobile crash safety standards have become stricter, performance requirements have improved, fuel efficiency has improved and CO 2 Due to demands for reducing emissions, it is necessary to achieve the conflicting performance requirements of increasing the strength of the vehicle body frame while reducing its mass, and the use of high-strength steel sheets in vehicle body components is continually increasing.

[0003] Automotive body components are often manufactured by cold press forming of steel sheets, which has high production efficiency and allows for mass production and low-cost manufacturing. However, as the strength of steel sheets increases, their press formability decreases, making them more susceptible to defects such as cracks (fractures), wrinkles, and poor shape and dimensional accuracy during press forming. For this reason, it is necessary to incorporate technical innovations into the press forming method and the shapes and mold shapes of the automotive body components from the design stage onwards in order to avoid defects during press forming.

[0004] However, if the thickness of the body components is reduced in order to reduce the weight of the car body, the rigidity of the body components or the rigidity of the entire car body will decrease. Therefore, it is not possible to uniformly increase the strength and reduce the thickness of all the body components. Which parts of the car body are strengthened or thinned, and how to design the optimal shape of the car body components according to the steel plate strength, are decided based on the experience of the engineers who design the car body and the accumulated technology that the vehicle manufacturers have cultivated. For this reason, it is common to learn and absorb the ingenuity, innovative technologies, and new material usage and construction methods seen in the design of the car bodies manufactured by each manufacturer through research of the car bodies on sale.

[0005] In such an investigation, an automobile body is disassembled at the joints between the body components, separated into individual body components, and a part of the steel plate, which is the material of the body components, is taken (sampled) to identify the characteristics of the steel plate by microscopic observation of hardness, plate thickness, and structure, and to perform comparative analysis. To identify the characteristics of the steel plate, for example, a steel plate taken from the body component is embedded in a resin molding material to prepare a test specimen, and the cross section of the steel plate embedded in the test specimen is mirror-polished to measure the plate thickness and hardness by the micro-Vickers method. Furthermore, the tensile strength (TS) of the steel plate is calculated from the measured hardness using a conversion formula. Then, by comparing these values ​​with the manufacturing standards, it becomes possible to identify the characteristics (standards, etc.) of the steel plate used in the body components.

[0006] A single automobile body has 300 to 500 body components, and the materials of each body component for each vehicle are compiled and stored in a material database. This material database is then used as the basis for various analytical investigations of the body components. Regarding the creation of a database for each vehicle, for example, Patent Document 1 discloses a technology in which a vehicle that is on sale is disassembled and data such as the materials of the parts used in the vehicle (strength, plate thickness, weight, dimensions, whether or not there is surface treatment, plating thickness, type of base (hot-rolled base or cold-rolled base), etc.), the number of spot welds, and images of the parts are stored. In this technology, when data on parts is stored, the data is classified by group names given to parts classified according to a standard that is uniform among multiple vehicles of different vehicle manufacturers or models, and part function names given based on the functions of the parts and that are uniform among multiple vehicles. This makes it possible to quickly extract parts to be compared and easily compare multiple vehicles of different vehicle manufacturers or models. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] Patent No. 5151380 Summary of the Invention [Problem to be solved by the invention]

[0008] For the body components of automobile bodies, steel sheets that have not been surface-treated (bare materials, JIS standards SPC, SPH, etc.) and plated surface-treated steel sheets (JISF standards SEC, SGC, etc.) are used. The plating applied to the surface-treated steel sheets includes zinc plating such as hot-dip galvanizing (GI), alloyed hot-dip galvanizing (GA), and electrolytic galvanizing (EG), and aluminum plating such as aluminum-silicon plating (Al-Si), which is a hot-dip aluminum plating. These surface-treated steel sheets are appropriately selected according to the required specifications such as rust prevention specifications, press formability, and painted appearance, and the adoption policy of each part or each vehicle manufacturer. In Japan, vehicle manufacturers mostly use GA for the majority of cold-pressed parts and Al-Si for hot-pressed parts, but overseas vehicle manufacturers often use GI or EG for cold pressing and Al-Si for hot pressing.

[0009] In creating a database for each vehicle, it is possible to store the type of plating on the surface-treated steel sheet as data related to the material of the part, as in the technology disclosed in Patent Document 1. To do so, it is necessary to take a sample of steel sheet for each vehicle body component and identify the type of plating applied to the steel sheet.

[0010] To identify the type of plating applied to a steel sheet, methods are used in which the components in the plating layer are quantified by wet analysis, or the element distribution in the plating layer is identified by spectroscopic analysis. As a method for wet analysis of a plating layer, there is a method in which the plating layer of a steel sheet is peeled off and dissolved with an alkaline solution or the like and then analyzed. Methods for spectroscopically analyzing the plating layer include X-ray spectroscopic analysis of the cross section of the plating layer using XPS (X-ray photoelectron spectroscopy) or EPMA (electron probe microanalyzer), or sputtering spectroscopic analysis such as GDS (glow discharge optical emission spectroscopy).

[0011] The method of identifying the element distribution of the plating layer by spectroscopic analysis has the advantage of being able to identify the plating type of the steel sheet non-destructively. On the other hand, spectroscopic analysis has the disadvantages of being very costly to measure and being time-consuming to prepare the analytical samples because the measurement is performed in a vacuum. In particular, since an automobile body usually has 300 to 500 body components per vehicle, identifying the plating type of the steel sheet used in the body components by the above-mentioned wet analysis or spectroscopic analysis requires huge measurement costs and effort.

[0012] The present invention has been made to solve the above-mentioned problems, and has an object to provide a method, device, and program for identifying the type of plating applied to steel sheets for automotive components, which can identify the type of plating applied to steel sheets of vehicle body components without requiring enormous measurement costs and effort. [Means for solving the problem]

[0013] (1) The method for identifying the type of plating applied to a steel sheet for an automobile according to the present invention is for identifying the type of plating applied to a steel sheet used for a body component of an automobile body, and includes the steps of: a steel plate cross-section grayscale image acquisition step of obtaining a steel plate cross-section grayscale image of the steel plate cross-section of the prepared test specimen by extracting a steel plate from the vehicle body component, taking an optical microscope photograph of a cross-section of the steel plate in the prepared test specimen, and acquiring a grayscale image of the taken optical microscope photograph; a grayscale histogram creation step of creating a histogram of the frequency of grayscale gradations for each pixel in the acquired grayscale image; and a plating type identifying step of identifying the type of plating applied to the steel sheet based on the distribution form of the created histogram.

[0014] (2) In the above (1), the grayscale image of the cross section of the steel plate includes a resin layer representing a resin that embeds and fixes the steel plate in the test specimen and / or a resin that is painted on a surface of the steel plate; The plating applied to the steel sheet is any one of hot-dip galvanizing, alloyed hot-dip galvanizing, electrolytic galvanizing, and hot-dip aluminum-based plating; In the plating type identification step, Selecting three peaks having large peak areas in the distribution of the histogram; The three selected peaks are designated as a first peak, a second peak and a third peak, which represent the following regions a, b and c, in ascending order of peak gradation value, determining whether or not a fourth peak exists between the first peak and the second peak in the distribution of the histogram, the fourth peak representing the following region d having a relatively small peak area; When it is determined that the fourth peak is present, if the relative position of the fourth peak is closer to the first peak than the second peak, the plating applied to the steel sheet is identified as electrogalvanized zinc; If the relative position of the fourth peak is closer to the second peak than the first peak, the coating applied to the steel sheet is identified as hot-dip galvanizing; When it is determined that the fourth peak does not exist, If the second peak and the third peak overlap, the coating applied to the steel sheet is identified as a hot-dip aluminum-based coating; When the second peak and the third peak are separated, the coating applied to the steel sheet is identified as alloyed hot-dip galvanizing. Region a: Region mainly consisting of grayscale gradations of cracks in the resin layer and plating layer Area b: Area dominated by the grayscale gradation of the steel substrate Area c: Area mainly composed of grayscale gradation of plating layer Area d: Area mainly consisting of grayscale gradations at the boundary between the coating layer and the base steel sheet

[0015] (3) In the above (2), In the plating type identification step, dividing the distribution of the histogram into a plurality of regions at gray scale gradations where the frequency of the histogram is minimal, thereby dividing the distribution of the histogram into peaks; The distribution of the histogram divided for each peak is approximated by a Gaussian function represented by the following formula (1): The coefficient a in the approximated formula (1) i and c i The product of these is calculated as the peak area of ​​the peak in each of the divided histograms, thereby selecting three peaks with the largest peak areas; determining whether or not the fourth peak exists based on whether or not there exists a histogram divided into peaks between the first peak and the second peak; The relative positional relationship between the fourth peak and the first and second peaks is expressed by the coefficient b i Determined by, The relative positional relationship between the second peak and the third peak is expressed by the coefficient b i and c i The present invention is characterized in that the discrimination is made by the following:

number

[0016] (4) The plating type identification device for automotive steel sheets according to the present invention is for identifying the type of plating applied to steel sheets used for vehicle body components of an automobile body, and is a steel plate cross-section grayscale image acquisition unit for acquiring a grayscale image of an optical microscope photograph of a steel plate cross-section in a test specimen including the steel plate sampled from the vehicle body component; a grayscale gradation histogram creation unit that creates a histogram of the frequency of grayscale gradations for each pixel in the acquired grayscale image; and a plating type identification unit that identifies the type of plating applied to the steel sheet based on the distribution form of the created histogram.

[0017] (5) The plating type identification program for automotive steel sheets according to the present invention is for identifying the type of plating applied to steel sheets used for vehicle body components of an automobile body, and includes the following steps: Computer, a steel plate cross-section grayscale image acquisition unit for acquiring a grayscale image of an optical microscope photograph of a steel plate cross-section in a test specimen including the steel plate sampled from the vehicle body component; a grayscale gradation histogram creation unit that creates a histogram of the frequency of grayscale gradations for each pixel in the acquired grayscale image; The present invention is characterized in that the device functions as a plating type identification unit that identifies the type of plating applied to the steel sheet based on the distribution form of the created histogram. Effect of the Invention

[0018] According to the present invention, a steel sheet is sampled from an automobile body component, and the type of plating can be identified using a grayscale image of an optical microscope photograph of the cross section of the steel sheet. This makes it possible to collect material information of each automobile body component that constitutes an automobile body and efficiently build a material database without performing instrumental analysis that requires huge measurement costs and labor to identify the type of plating applied to the steel sheet. [Brief description of the drawings]

[0019] [Figure 1] FIG. 1 is a flow chart showing a process flow in a method for identifying the type of plating on automotive steel sheets according to an embodiment of the present invention. [Diagram 2] FIG. 1 is a diagram illustrating items showing physical and chemical properties of a plating layer in an optical microscope photograph of a cross section of a plated steel sheet, explaining how the present invention was arrived at. [Diagram 3]FIG. 1 is a diagram for explaining the correspondence between the distribution form of a grayscale histogram created from grayscale image digital data of an optical microscope photograph of a steel sheet cross section and the type of plating applied to the steel sheet in the process of arriving at the present invention (dashed line: distribution in which each peak is approximated by a Gaussian function, solid line: histogram distribution in which peaks approximated by a Gaussian function for each region are superimposed). [Figure 4] FIG. 1 is a diagram illustrating a configuration of an automotive steel sheet plating type identification device and a program according to an embodiment of the present invention. [Diagram 5] FIG. 2 is a diagram illustrating a flow for identifying the type of plating applied to a steel sheet sampled from a vehicle body component by elemental analysis in an embodiment. [Figure 6] In the examples, the results show the distribution of grayscale histograms created by the plating type identification method according to the present invention for steel sheets whose plating type was identified by conventional instrumental analysis ((a) hot-dip galvanized, (b) electrolytic galvanized, (c) alloyed hot-dip galvanized, (d) aluminum-silicon plating, which is a hot-dip aluminum-based plating). DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0020] Before describing the method, device, and program for identifying the type of plating on automotive steel sheets according to the embodiments of the present invention, the background to the invention will be described.

[0021] <Background to the invention> In order to identify the material properties (strength and specifications) of steel sheets used in vehicle body components, it is essential to extract steel sheets from the vehicle body components and embed the extracted steel sheets in resin to prepare test specimens for benchmarking vehicle body components and building a material database. In identifying the material properties of steel sheets using such test specimens, optical microscope photographs of a portion of the test specimen including a cross section of the steel sheet (hereinafter referred to as "steel sheet cross section" in this application) were taken, and the thickness of the steel sheet was measured, the presence or absence of a plating layer was observed, and the thickness of the plating layer was measured, etc.

[0022] Therefore, the inventors considered that there would be benefits in terms of time and cost if it were possible to identify the type of plating from an optical microscope photograph of the cross section of a steel sheet.Furthermore, in order to identify the type of plating from an optical microscope photograph of the cross section of a steel sheet, it was considered important to clarify the relationship between the items that represent the physical and chemical properties of the plating layer in the optical microscope photograph and the type of plating.

[0023] Therefore, the inventors have conducted extensive research into the factors that indicate the characteristics of a coating layer in an optical microscope photograph of a steel sheet cross section, and have identified the following four factors (1) to (4). Each of factors (1) to (4) will be explained below in relation to the optical microscope photograph of the steel sheet cross section shown in FIG.

[0024] (1) Morphology of the plating layer The morphological characteristics of the plating layer include multiple crystal compositions and eutectic structures found in the inhomogeneous plating layer, and cracks that occur in the plating layer due to press forming processing.

[0025] The inhomogeneous plating layer has a morphology characteristic of the eutectic structure of aluminum-silicon plating (Al-Si, Fig. 2(d)), which is a molten aluminum-based plating after hot press forming, and cracks and voids are observed. In addition, the coating layer in which the cracks occurred is a morphology commonly seen in galvannealed coatings (GA, Figure 2(a)), which is caused by a decrease in the ductility of the Zn-Fe alloy crystals formed by the alloying process.

[0026] In contrast, in the coating layers of hot-dip galvanized (GI) and electrogalvanized (EG) steel sheets, as shown in Figures 2(b) and (c), no eutectic structure or cracks were observed in the coating layers, and the morphology of the coating layers was found to be homogeneous.

[0027] (2) Change in contrast at the boundary between the base steel sheet and the coating layer In optical microscope photographs of the cross section of a steel sheet, a contrast change (a change in grayscale gradation in the case of a grayscale image) is observed in the area corresponding to the boundary between the steel sheet substrate (base steel sheet) and the coating layer. Such a contrast change is presumed to be due to the presence or absence of a continuous component diffusion layer between the steel sheet substrate and the coating layer.

[0028] Since galvannealed (GA) coating has a continuous Fe-Al-Zn diffusion layer, as shown in Figure 2(a), although there is a difference in the contrast (grayscale gradation) between the base steel sheet and the coating layer, the boundary between the coating layer and the base steel sheet is unclear. In contrast, hot-dip galvanized (GI) and electro-galvanized (EG) coatings do not have a chemically-dispersed layer, and therefore have the characteristic that there is a clear change in contrast at the boundary between the base steel sheet and the coating layer, as shown in Figures 2(b) and (c). In addition, with aluminum-silicon plating (Al-Si), a molten aluminum-based coating, the color tones (grayscale gradation) of the base steel sheet and the coating layer are almost the same, as shown in Figure 2(d), so the change in contrast at the boundary is unclear.

[0029] (3) Ability to conform to the shape of the substrate steel The ability to conform to the shape of the substrate steel sheet refers to the effect of the surface shape (irregularities) of the substrate steel sheet on the irregularities of the coating layer surface. Hot-dip galvanizing (GI) is a process in which a steel sheet is immersed in molten zinc and then pulled up. As a result, as shown in Figure 2(b), the surface tension of the liquid molten zinc before solidification makes the surface of the coating layer smooth and it is less affected by the surface shape of the steel sheet. In contrast, with electrolytic galvanization (EG), electrodeposition occurs along the contours of the base steel sheet, resulting in an almost constant thickness of the plating layer, as shown in Figure 2(c), and the influence of the surface shape of the base steel sheet is reflected in the surface contours of the plating layer.

[0030] (4) Combination of surface roughness and shape As shown in Figure 2(c), the surface of electrolytic galvanized (EG) plating is covered with step-like electrolytic Zn crystals. Therefore, when observing the cross section of an electrolytic galvanized steel sheet, a characteristic step-like shape can be seen on the outermost surface.

[0031] In the study, the inventors noticed that, with regard to item (2) (change in contrast at the boundary between the base steel sheet and the plating layer), characteristic differences were observed in the contrast change in grayscale images of optical microscope photographs of the cross sections of steel sheets depending on the type of plating, and came up with the idea of ​​evaluating the contrast change in grayscale images as differences in the distribution form of histograms of the occurrence frequency of grayscale gradations.

[0032] FIG. 3 shows histograms created by integrating the frequency of occurrence of grayscale gradations for each pixel in grayscale images of optical microscope photographs of the cross sections of steel sheets with various platings.

[0033] In Figure 3, (a) is a histogram of grayscale gradation created from grayscale images of the cross section of a steel sheet that has been treated with alloy hot-dip galvanizing (GA), (b) is a hot-dip galvanizing (GI), (c) is an electrolytic galvanizing (EG), and (d) is an aluminum-silicon plating (Al-Si), which is a hot-dip aluminum-based plating.

[0034] In the histograms of galvannealed (GA), hot-dip galvanized (GI) and electrogalvanized (EG) coatings, the coating layer has the highest grayscale gradation (white) and the resin has the lowest grayscale gradation (black) as shown in Figures 3(a) to (c). Furthermore, the grayscale gradation of the base steel sheet is intermediate between that of the coating layer and that of the resin.

[0035] Furthermore, the histograms for hot-dip galvanized (GI) and electro-galvanized (EG) show that, as shown in Figures 3(b) and 3(c), there is a boundary between the plating layer and the base steel sheet between the resin and the base steel sheet (A in Figure 3(b) and B in Figure 3(c)). However, in hot-dip galvanized (GI) coating, the boundary between the coating layer and the base steel sheet has a grayscale tone close to that of the base steel sheet, as shown in Fig. 3(b), whereas in electrolytic galvanized (EG) coating, the boundary between the coating layer and the base steel sheet has a grayscale tone close to that of resin, as shown in Fig. 3(c).

[0036] As shown in Fig. 2(a) above, in the case of galvannealed hot-dip galvanizing (GA), no clear boundary is observed between the coating layer and the base steel sheet. Therefore, in the histogram of galvannealed hot-dip galvanizing (GA), as shown in Fig. 3(a), no small peak is observed between the peak of the grayscale gradation representing the coating layer and the peak of the grayscale gradation representing the base steel sheet.

[0037] As shown in Figure 2(d), aluminum silicon plating (Al-Si), which is a molten aluminum-based coating, has almost the same grayscale gradation of the base steel sheet and the coating layer, making it difficult to recognize the boundary between the two. Therefore, the histogram of aluminum silicon plating shows a distribution in which the grayscale gradations representing the coating layer and the base steel sheet overlap, as shown in Figure 3(d). However, the grayscale gradation representing the coating layer is characterized by the presence of two peaks with different grayscale gradations (E and E in Figure 3(d)).

[0038] Furthermore, it was found that when optical microscope photographs taken at the same magnification have the same field of view and size, and the contrast is adjusted so that the grayscale gradations of the resin and plating layer are at opposite ends of the spectrum, the histogram of grayscale gradations takes on a characteristic distribution pattern depending on the type of plating.

[0039] The present invention has been made based on the above findings, and the specific configuration thereof will be described below.

[0040] <How to identify plating type> The plating type identifying method for automotive steel sheets according to this embodiment (hereinafter referred to as the "plating type identifying method") identifies the type of plating applied to steel sheets used in vehicle body components of automobile bodies. As shown in Fig. 1, the plating type identifying method according to this embodiment includes a steel sheet cross-section grayscale image acquiring step S1, a grayscale gradation histogram creating step S3, and a plating type identifying step S5. Hereinafter, each of the above steps will be described for the case where the plating applied to the steel sheet is any one of hot-dip galvanizing, alloyed hot-dip galvanizing, electrolytic galvanizing, and aluminum-silicon plating, which is a hot-dip aluminum-based plating.

[0041] <Steel plate cross-section grayscale image acquisition process> The steel plate cross-section grayscale image acquisition process S1 is a process in which a steel plate is taken from a vehicle body component to prepare a test specimen including the steel plate, an optical microscope photograph of the cross section of the steel plate in the prepared test specimen is taken, and a grayscale image of the taken optical microscope photograph is obtained.

[0042] The test specimen can be prepared by embedding and fixing the collected steel plate in a resin for optical microscope observation. As the resin, for example, a heat-curing type epoxy resin or a room temperature curing type carbon-added acrylic resin can be used, and the type of resin is not particularly limited as long as it is black in color after curing.

[0043] After the resin in which the steel sheet is embedded has hardened, the cross section of the steel sheet of the test specimen should be mirror-polished before being observed under an optical microscope. Note that etching, which is commonly performed for the purpose of observing the structure of the steel sheet, is desirably not applied to the test specimen of the present invention because it may affect the plating layer applied to the steel sheet.

[0044] <Grayscale gradation histogram creation process> The grayscale gradation histogram creation step S3 is a step of creating a histogram of the frequency of grayscale gradation for each pixel in the grayscale image acquired in the steel sheet cross-section grayscale image acquisition step S1.

[0045] <Plating type identification process S5> The plating type identifying step S5 is a step of identifying the type of plating applied to the steel sheet based on the distribution form of the histogram created in the grayscale gradation histogram creating step S3.

[0046] Specific examples of identifying the type of plating in the plating type identifying step S5 include the following examples A and B.

[0047] (Aspect A) In the embodiment A, first, three peaks with large peak areas in the histogram distribution are selected. The histogram peak refers to a mountain-shaped distribution curve including one maximum value in the histogram distribution, and the peak area refers to the area of ​​the range surrounded by the mountain-shaped distribution curve. The selection of the three peaks with large peak areas may be performed, for example, by visual inspection by an operator, or may be performed by calculating the area surrounded by the mountain-shaped distribution curve of each peak in the histogram distribution.

[0048] Next, the three selected peaks are designated as the first peak, the second peak, and the third peak, which represent the following regions a, b, and c, in ascending order of peak gradation value, where the peak gradation value refers to the grayscale gradation value at the center position of each peak. Region a: Region mainly consisting of grayscale gradations of cracks and voids in the resin layer and plating layer Area b: Area dominated by the grayscale gradation of the steel substrate Area c: Area mainly composed of grayscale gradation of plating layer

[0049] Next, the presence or absence of a fourth peak representing the following region d, in which the peak area is relatively small, between the first and second peaks in the histogram distribution is determined. Area d: Area mainly consisting of grayscale gradations at the boundary between the coating layer and the base steel sheet

[0050] (A-1) When it is determined that there is a fourth peak In this case, the coating applied to the steel sheet is identified as hot-dip galvanizing or electro-galvanizing based on the relative positions of the fourth peak and the first or second peak. If the relative position of the fourth peak is closer to the first peak than to the second peak, the plating applied to the steel sheet is identified as electrolytic zinc plating. On the other hand, if the relative position of the fourth peak is closer to the second peak than to the first peak, the coating applied to the steel sheet is identified as hot-dip galvanizing.

[0051] In this way, the type of plating can be identified based on the relative positions of the fourth peak and the first or second peak due to the aforementioned identification item for plating types, “(2) Change in contrast at the boundary between the base steel sheet and the plating layer.” In other words, as shown in Figure 3(c), the boundary between the electrolytic zinc plating layer and the base steel sheet has a grayscale gradation close to that of resin, which means that the relative position of the fourth peak is close to that of the first peak. In contrast, as shown in Figure 3(b), the boundary between the coating layer and the base steel sheet in hot-dip galvanized (GI) has a grayscale gradation close to that of the base steel sheet, which means that the relative position of the fourth peak is close to the second peak.

[0052] As the relative position of the fourth peak and the first or second peak, the absolute value of the difference between the peak gradation values ​​of each peak can be used. If the absolute value of the difference between the peak gradation value of the fourth peak and the peak gradation value of the first peak is smaller than the absolute value of the difference between the peak gradation values ​​of the fourth peak and the second peak, it indicates that the relative position of the fourth peak is closer to the first peak than the second peak. In contrast, if the absolute value of the difference between the peak gradation value of the fourth peak and the peak gradation value of the first peak is greater than the absolute value of the difference between the peak gradation values ​​of the fourth peak and the second peak, this indicates that the relative position of the fourth peak is closer to the second peak than to the first peak.

[0053] (A-2) When it is determined that there is no fourth peak In this case, the coating applied to the steel sheet is identified as either alloyed hot-dip galvannealing or aluminum-silicon coating, which is a hot-dip aluminum-based coating, based on the relative positions of the second and third peaks. As the relative positions of the second and third peaks, the absolute value of the difference in peak gradation value of each peak can be used, similar to the relative positions of the fourth peak and the first or second peak described above.

[0054] When the absolute value of the difference between the peak gradation value of the second peak and the peak gradation value of the third peak is small, the second peak and the third peak are close to each other and overlap, so the coating applied to the steel sheet is identified as aluminum silicon coating (Al-Si), which is a molten aluminum-based coating. This is because, in aluminum silicon coating (Al-Si), the grayscale gradations of the base steel sheet and the coating layer are almost equal, and the distribution of grayscale gradations indicating the coating layer overlaps with the distribution of grayscale gradations indicating the base steel sheet (Figure 3(d)).

[0055] In contrast, when the absolute value of the difference between the peak gradation value of the second peak and the peak gradation value of the third peak is large, the second peak and the third peak are far apart and separated, and the coating applied to the steel sheet is identified as galvannealed (GA). This is because in galvannealed (GA) coating, there is a difference in the contrast (grayscale gradation) between the base steel sheet and the coating layer (Figure 3(a)).

[0056] [Aspect B] In the embodiment B, first, the histogram distribution is divided into a plurality of regions at the gray scale gradation where the frequency of the histogram is at a minimum, thereby dividing the histogram distribution into peaks. Then, the distribution of the histogram divided for each peak is approximated by a Gaussian function expressed by the following formula (1).

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[0057] Next, the coefficient a in the approximated equation (1) i and c i The product of these is calculated as the peak area of ​​peak i in the divided histogram. In this way, the peak areas of all peaks in the histogram are calculated, and the three peaks with the largest peak areas are selected. Then, similarly to the above-described embodiment A, the three selected peaks are designated as a first peak, a second peak, and a third peak in ascending order of peak gradation value. Furthermore, the presence or absence of a fourth peak having a small peak area between the first and second peaks is determined.

[0058] (B-1) When it is determined that there is a fourth peak In this case, similarly to the above-mentioned mode A, the coating applied to the steel sheet is identified as hot-dip galvanizing or electrolytic galvanizing based on the relative positions of the fourth peak and the first or second peak. Here, the coefficient b i Since represents the center position of the peak, the relative positional relationship between the fourth peak, the first peak, and the second peak is expressed by the coefficient b i It can be distinguished by:

number

[0059] When formula (2-1) is satisfied, the relative position of the fourth peak is closer to the first peak than to the second peak, and therefore the type of plating can be identified as electrogalvanized (EG) (see Figure 3(c)).

[0060] When formula (2-2) is satisfied, the relative position of the fourth peak is closer to the second peak than to the first peak, and therefore the type of coating can be identified as hot-dip galvanized (GI) (see Figure 3(b)).

[0061] (B-2) When it is determined that there is no fourth peak In this case, the coating applied to the steel sheet is identified as a galvannealed coating or an aluminum-silicon coating, which is a hot-dip aluminum-based coating, based on the relative positions of the second and third peaks. Here, the relative positional relationship between the second and third peaks is expressed by the coefficient b i and c i It can be determined using the following:

number

[0062] Equation (3) represents the peak resolution between the second and third peaks. When formula (3) is satisfied, that is, when the peak separation between the second and third peaks is low, it indicates that the second and third peaks are close to each other and overlap, and the type of plating is identified as aluminum silicon plating (Al-Si), which is a molten aluminum-based plating (see Figure 3(d)). On the other hand, when formula (3) is not satisfied, that is, when the peak separation between the second and third peaks is high, it indicates that the second and third peaks are far apart and separated, and the type of coating is identified as galvannealed (GA) (see Figure 3(d)).

[0063] In addition, in the formula (3), the coefficient on the right side (=1.1774) is a numerical value given as an example of an index of the degree of peak separation, and can be appropriately given according to the contrast of the grayscale image.

[0064] As described above, according to the method for identifying the type of plating on automotive steel sheets according to the present embodiment, a steel sheet is sampled from an automotive body component, and the type of plating applied to the steel sheet can be identified using a grayscale image of an optical microscope photograph of the cross section of the steel sheet. This makes it possible to collect material information on each of the automotive body components that make up the automotive body and efficiently build a material database without performing instrumental analysis that requires huge measurement costs and labor to identify the type of plating applied to the steel sheet.

[0065] <Plating type identification device> The plating type identification device 1 for automotive steel sheets according to an embodiment of the present invention (hereinafter referred to as "plating type identification device 1") identifies the type of plating applied to steel sheets used in vehicle body components of automobile bodies. As an example, as shown in Fig. 4, the plating type identification device 1 includes a steel sheet cross-section grayscale image acquisition unit 11, a grayscale gradation histogram creation unit 13, and a plating type identification unit 15. The plating type identification device 1 may be configured by a CPU (Central Processing Unit) of a computer (such as a PC). In this case, the above-mentioned units function as a result of the CPU of the computer executing a predetermined program.

[0066] <Steel plate cross-section grayscale image acquisition unit> The steel plate cross-section grayscale image acquisition unit 11 acquires a grayscale image of an optical microscope photograph of a steel plate cross section in a test specimen including a steel plate taken from a vehicle body component.

[0067] <Grayscale gradation histogram creation section> The grayscale gradation histogram creation unit 13 creates a histogram of the frequency of grayscale gradation for each pixel in the grayscale image acquired by the steel plate cross-section grayscale image acquisition unit 11.

[0068] <Plating type identification section> The plating type identification unit 15 identifies the type of plating applied to the steel sheet based on the distribution form of the histogram created by the grayscale gradation histogram creation unit 13.

[0069] Specifically, the plating type identifying unit 15 may identify the plating type by a procedure similar to that of aspect B of the plating type identifying step S5 of the plating type identifying method according to the present embodiment described above.

[0070] First, the histogram distribution is divided into multiple regions at the grayscale gradation where the histogram frequency is at a minimum, and the histogram distribution divided into peaks is then approximated by the Gaussian function expressed by the above-mentioned equation (1).

[0071] Next, the coefficient a in equation (1) that approximates the distribution of the histogram divided by peaks is i and c i The three peaks having the largest product (=peak area) are selected, and the selected three peaks are designated as a first peak, a second peak, and a third peak in order of decreasing peak gradation value.

[0072] Next, the presence or absence of a fourth peak is determined based on the presence or absence of a histogram distribution divided into peaks between the first and second peaks.

[0073] If it is determined that the fourth peak is present, the coating applied to the steel sheet is identified as hot-dip galvanized or electro-galvanized based on the relative positions of the fourth peak and the first or second peak. The relative positions of the fourth peak and the first and second peaks are determined by the above-mentioned formulas (2-1) and (2-1).

[0074] If it is determined that the fourth peak does not exist, the coating applied to the steel sheet is identified as a hot-dip galvannealed coating or an aluminum-silicon coating, which is a hot-dip aluminum-based coating, based on the relative positions of the second and third peaks. The relative positional relationship between the second and third peaks is determined by the above-mentioned formula (3).

[0075] <Plating type identification program> An embodiment of the present invention can be configured as a plating type identification program for automotive steel sheets (hereinafter, "plating type identification program"). That is, the plating type identification program according to the present embodiment is for identifying the type of plating applied to a steel sheet used for a vehicle body component of an automobile body. As an example, as shown in Fig. 4, the plating type identification program has a function of causing a computer to execute a steel sheet cross-section grayscale image acquisition unit 11, a grayscale gradation histogram creation unit 13, and a plating type identification unit 15.

[0076] As described above, the plating type identification device and program for automotive steel sheets according to the present embodiment can also identify the plating type using a grayscale image of an optical microscope photograph of a cross section of a steel sheet taken from an automotive body component. This makes it possible to collect material information for each automotive body component that constitutes an automotive body and efficiently build a material database without performing instrumental analysis that requires huge measurement costs and effort.

[0077] In addition, when there are differences in the greyscale gradations of the resin, the base steel sheet, and the plating layer in the greyscale image of the optical microscope photograph of the cross section of the steel sheet, three peaks representing the resin, the base steel sheet, and the plating layer are clearly seen in the histogram of the frequency of the greyscale gradations in the greyscale image.

[0078] However, depending on the contrast of the grayscale image, a histogram distribution may be obtained in which a peak representing the steel substrate and a peak representing the coating layer overlap. In such a case, in order to select the peaks representing the steel substrate and the coating layer from the overlapping peaks, it is possible to select each of the two peaks by approximating the two distributions represented by the Gaussian function described above as being overlapping.

[0079] In addition, in this embodiment, the type of plating applied to steel sheets used for vehicle body components of automobile bodies is any one of hot-dip galvanizing, electrolytic galvanizing, alloyed hot-dip galvanizing, and aluminum-silicon plating, which is a hot-dip aluminum-based plating. This is because steel sheets plated with the above four types of plating are used for almost all of the vehicle body components on the market. Therefore, in identifying the type of plating of automotive steel sheets according to the present invention, there is no particular problem even if it is any one of the above four types of plating.

[0080] However, even if a steel sheet plated with a plating other than the above four types is used for a vehicle body component, it has been confirmed that such a plated steel sheet has a different grayscale gradation distribution pattern in the cross section of the steel sheet from that of the above four types of plating. Therefore, according to the present invention, it is possible to identify plating types other than the above four types based on the distribution pattern of a grayscale gradation histogram created from a grayscale image of an optical microscope photograph of the cross section of the steel sheet.

[0081] In the above explanation, the optical microscope photograph of the cross section of the steel sheet includes the resin in which the steel sheet was embedded and fixed when the test specimen was prepared, but in the present invention, the photograph may include a resin that is painted on the surface of the steel sheet. Even in such a case, since the resin is black, it does not cause any problem in identifying the type of plating applied to the steel sheet according to the present invention.

[0082] In the present invention, a digital camera such as a CCD camera can be suitably used to take an optical microscope photograph of the cross section of the steel sheet, whereby the taken optical microscope photograph can be obtained as digital data of a grayscale image.

[0083] However, the present invention may also be such that an optical microscope photograph of a steel sheet cross section taken with a digital camera is obtained as digital data of a color image, and then the digital data is converted into digital data of a grayscale image.

[0084] The grayscale image may have a grayscale gradation of 8 bits (256 gradations) or more, and may be digital data of a high-definition grayscale image such as 16 bits (65,536 gradations). If the grayscale gradation is smaller than 8 bits, there is a risk that it will be impossible to identify, for example, aluminum silicon plating, which is a molten aluminum-based plating after hot press forming.

[0085] In addition, the optical microscope photograph of the cross section of the steel sheet taken with a digital camera preferably has a magnification of about 1000 to 2000. This is because, although the resolution improves with a higher magnification, the range (field of view) of the image is reduced, and there is a concern that the image may not provide average information of the entire plating layer on the cross section of the steel sheet.

[0086] Furthermore, the resolution of the digital camera is important along with the magnification of the optical microscope photograph, but there are no particular limitations as long as it is suitable for the magnification of the optical microscope photograph, and a digital camera with a pixel count of approximately 1.0M to 10.0M pixels can be suitably used.

[0087] In the present invention, in order to accurately identify the type of plating using a grayscale image of an optical microscope photograph including a steel sheet cross section, it is preferable to make the contrast of the grayscale image uniform. Usually, in a grayscale image of an optical microscope photograph in which a plated steel sheet is embedded in black resin and photographed, the area corresponding to the resin is the darkest (black), the plating layer is the lightest (white), and the base steel sheet is intermediate (gray). However, aluminum-silicon plating, which is a molten aluminum-based plating, is different from other platings in that the grayscale gradation of the plating layer is an intermediate color with little difference from the base steel sheet. Considering this, it is preferable to adjust the contrast of the grayscale image based on the black part of the resin and the intermediate color part of the base steel sheet.

[0088] It is desirable to adjust the contrast of a greyscale image so that, assuming the full scale of the greyscale gradation is 100% (0% = black, 100% = white), the black areas corresponding to the resin are 5 to 10% and the intermediate colour areas of the underlying steel sheet are 50%.

[0089] The reason why the grayscale gradation of the black parts corresponding to the resin is not set to 0% is to prevent excessive contrast expansion adjustment, which can cause so-called "black crush" and reduce the accuracy of identifying the plating type. Furthermore, by adjusting the contrast as described above, it is difficult to expand the width of the intermediate color and black parts too much, so "whiteout" of the white parts can also be suppressed at the same time.

[0090] For these reasons, in the present invention, it is advisable to take an optical microscope photograph of the cross section of a steel sheet by adjusting the contrast so that the distribution of the histogram of the grayscale image falls within the range of 3% to 97% of the full scale. EXAMPLES

[0091] Experiments were carried out to confirm the effects of the present invention, and these will be described below.

[0092] In the experiment, five passenger cars were procured, dismantled, and the body components of the car body were disassembled and examined. From the body components that make up the body-in-white structure of the car body, 200 main parts weighing 100g or more per car were taken as steel plates and embedded in epoxy resin to create test specimens. The cross section of the steel plate embedded in the test specimen was then polished, and optical microscope photographs of the steel plate cross section were taken with a 1500x optical magnification, 4-megapixel CCD camera.

[0093] Next, the optical microscope photographs were acquired as digital data of grayscale images (8 bit, 256 gradations) and stored in a storage device together with the identification codes assigned to each vehicle component part. The types of plating applied to the steel sheets used in the target vehicle body components were identified by the conventional instrumental analysis (EPMA elemental analysis) described in the subject of this application, following the procedure shown in Fig. 5. The vehicle body components surveyed in this example included all four types of plating, namely, electrolytic galvanization (EG), hot-dip galvanization (GI), alloyed hot-dip galvanization (GA), and aluminum-silicon plating (Al-Si, hot-formed parts), which is a molten aluminum-based plating, and no other plating types were used.

[0094] Of the 1,000 vehicle body components surveyed (for five passenger cars), steel plates were taken from 730 vehicle body components determined to contain steel plates, and each steel plate was embedded and fixed in resin to create test specimens. Then, the prepared test specimen was used to obtain a grayscale image of an optical microscope photograph of the cross section of the steel plate.

[0095] Furthermore, for each acquired grayscale image, the grayscale gradation of each pixel in the range of 410 to 620 pixels in the cross-sectional depth direction of the steel plate, with the center of the plating layer as the center, and 2048 pixels in the direction perpendicular to the cross-sectional depth direction were collected, and a histogram of the frequency of the grayscale gradation was created.

[0096] Figure 6 shows a histogram distribution of grayscale gradation created from a grayscale image of an optical microscope photograph of a steel sheet cross section whose plating type was identified by conventional instrumental analysis. The dashed lines in Figure 6 are distributions approximated by formula (1) for the first peak (resin), the second peak (base steel sheet), the third peak (plating layer), and the fourth peak (boundary portion) selected from the histogram distribution. The gray solid line in Figure 6 represents the distribution of the histogram of grayscale gradation in the grayscale image by superimposing the first peak, second peak, third peak, and fourth peak.

[0097] Table 1 also shows the coefficients a, b, c, and d, which were calculated by approximating the Gaussian function of the above-mentioned formula (1) for the first, second, third, and fourth peaks selected from the distribution of the histograms created for each plating type. i , b i and c i In Table 1, the resin represents the first peak, the base steel sheet represents the second peak, the plating layer represents the third peak, and the boundary portion represents the fourth peak.

[0098] [Table 1]

[0099] Furthermore, Table 2 shows the results of determining the presence or absence of a fourth peak in the distribution pattern of the histograms for each plating type shown in Figures 6(a) to (d), the degree of separation between the second and third peaks calculated by the above-mentioned formula (3), and the relative positions of the fourth peak and the first peak.

[0100] [Table 2]

[0101] The peak resolution between the second and third peaks shown in Table 2 is calculated according to the above formula (3), (b 3 -b 2 )-1.174(c 3 +c2 ) When the peak resolution is positive, it means that the second and third peaks are separated, and when the peak resolution is negative, it means that the second and third peaks are not separated but overlap.

[0102] The relative position of the fourth peak shown in Table 2 is calculated by |b 2 -b 4 |-|b 4 -b 1 When the relative position of the fourth peak is positive, the relative position of the fourth peak is closer to the first peak, and when the relative position of the fourth peak is negative, the relative position of the fourth peak is closer to the second peak.

[0103] The histogram shown in Fig. 6(a) shows that there is a fourth peak between the first and second peaks, and the relative position of the fourth peak is a negative value, which indicates that the relative position of the fourth peak is close to the second peak. Therefore, the distribution form of this histogram indicates that the type of coating applied to the steel sheet is hot-dip galvanized (GI), which is consistent with the coating type identified by instrumental analysis.

[0104] The histogram shown in Figure 6(b) shows that there is a fourth peak between the first and second peaks, and the relative position of the fourth peak is a positive value, which indicates that the relative position of the fourth peak is close to the first peak. Therefore, the distribution form of this histogram indicates that the type of plating applied to the steel sheet is electrogalvanized (EG), which is consistent with the plating type identified by instrumental analysis.

[0105] The histogram shown in Figure 6(c) shows that the second and third peaks are separated from each other because there is no fourth peak between the first and second peaks and the degree of separation between the second and third peaks is a positive value. Therefore, the distribution form of this histogram indicates that the type of coating applied to the steel sheet is galvannealed (GA), which is consistent with the type of coating identified by instrumental analysis.

[0106] The histogram shown in Figure 6(d) shows that there is no fourth peak between the first and second peaks, and the degree of separation between the second and third peaks is a negative value, indicating that the second and third peaks are not separated but overlap. Therefore, the distribution form of this histogram indicates that the type of coating applied to the steel sheet is aluminum silicon coating (Al-Si), which is a hot-dip aluminum-based coating, and matches the type of coating identified by instrumental analysis.

[0107] In this way, the plating type was identified using grayscale images of optical microscope photographs of the cross sections of steel sheets sampled from vehicle body components, with the instrumental analysis and identification information of the plating type concealed (masked). As a result, the plating type could be accurately identified for all sampled steel sheets. Therefore, it was demonstrated that the present invention makes it possible to accurately identify the type of plating applied to steel sheets used in vehicle body components of automobile bodies, without performing instrumental analysis that requires cost and effort. [Explanation of symbols]

[0108] 1. Plating type identification device 11 Steel plate cross-section grayscale image acquisition unit 13 Grayscale gradation histogram creation section 15 Plating type identification section

Claims

1. A method for identifying the type of plating applied to a steel sheet used for a vehicle body component of an automobile body, comprising: a steel plate cross-section grayscale image acquisition step of obtaining a steel plate cross-section grayscale image of the steel plate cross-section of the prepared test specimen by extracting a steel plate from the vehicle body component, taking an optical microscope photograph of a cross-section of the steel plate in the prepared test specimen, and acquiring a grayscale image of the taken optical microscope photograph; a grayscale histogram creation step of creating a histogram of the frequency of grayscale gradations for each pixel in the acquired grayscale image; and a plating type identifying step of identifying the type of plating applied to the steel sheet based on the distribution form of the created histogram.

2. the grayscale image of the cross section of the steel plate includes a resin layer representing a resin that embeds and fixes the steel plate in the test specimen and / or a resin that is painted on a surface of the steel plate; The plating applied to the steel sheet is any one of hot-dip galvanizing, alloyed hot-dip galvanizing, electrolytic galvanizing, and hot-dip aluminum-based plating; In the plating type identification step, Selecting three peaks having large peak areas in the distribution of the histogram; The three selected peaks are designated as a first peak, a second peak and a third peak, which represent the following regions a, b and c, in ascending order of peak gradation value: determining whether or not a fourth peak exists between the first peak and the second peak in the distribution of the histogram, the fourth peak representing the following region d having a relatively small peak area; When it is determined that the fourth peak is present, if the relative position of the fourth peak is closer to the first peak than to the second peak, the plating applied to the steel sheet is identified as electrogalvanized zinc; If the relative position of the fourth peak is closer to the second peak than the first peak, the coating applied to the steel sheet is identified as hot-dip galvanizing; When it is determined that the fourth peak does not exist, If the second peak and the third peak overlap, the coating applied to the steel sheet is identified as a hot-dip aluminum-based coating; 2. The method for identifying a type of coating on an automotive steel sheet according to claim 1, wherein, when the second peak and the third peak are separated, the coating applied to the steel sheet is identified as a galvannealed coating. Region a: Region mainly consisting of grayscale gradations of cracks in the resin layer and plating layer Region b: Region mainly consisting of the grayscale gradation of the base steel sheet Region c: Region mainly composed of grayscale gradation of plating layer Region d: Region mainly consisting of grayscale gradation at the boundary between the coating layer and the base steel sheet

3. In the plating type identification step, dividing the distribution of the histogram into a plurality of regions at gray scale gradations where the frequency of the histogram is minimal, thereby dividing the distribution of the histogram into peaks; The distribution of the histogram divided for each peak is approximated by a Gaussian function represented by the following formula (1): The coefficient a in the approximated formula (1) i and c i The product of these is calculated as the peak area of ​​the peak in each of the divided histograms, thereby selecting three peaks with the largest peak areas; determining whether or not the fourth peak exists based on whether or not there exists a histogram divided into peaks between the first peak and the second peak; The relative positional relationship between the fourth peak and the first and second peaks is expressed by the coefficient b i Determined by, The relative positional relationship between the second peak and the third peak is expressed by the coefficient b i and c i 3. The method for identifying the type of plating on steel sheets for automobiles according to claim 2, further comprising the steps of: [0010]

4. A plating type identification device for automotive steel sheets that identifies the type of plating applied to steel sheets used for vehicle body components of an automobile body, comprising: a steel plate cross-section grayscale image acquisition unit for acquiring a grayscale image of an optical microscope photograph of a steel plate cross-section in a test specimen including the steel plate sampled from the vehicle body component; a grayscale gradation histogram creation unit that creates a histogram of the frequency of grayscale gradations for each pixel in the acquired grayscale image; and a plating type identification unit that identifies the type of plating applied to the steel sheet based on the distribution form of the created histogram.

5. A plating type identification program for an automotive steel sheet for identifying a type of plating applied to a steel sheet used for a body component of an automobile body, comprising: Computer, a steel plate cross-section grayscale image acquisition unit for acquiring a grayscale image of an optical microscope photograph of a steel plate cross-section in a test specimen including the steel plate sampled from the vehicle body component; a grayscale gradation histogram creation unit that creates a histogram of the frequency of grayscale gradations for each pixel in the acquired grayscale image; A plating type identification program for automotive steel sheets, characterized in that the program functions as a plating type identification unit that identifies the type of plating applied to the steel sheet based on the distribution pattern of the created histogram.

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