Method for measuring the shape of a strip-like object, method for controlling the shape of a strip-like object, method for manufacturing a strip-like object, quality control method for a strip-like object, device for measuring the shape of a strip-like object, and manufacturing equipment for a strip-like object

Abstract

The shape measurement method for a strip-like object is a shape measurement method for measuring the shape of a strip-like object, and includes an imaging step of capturing an image of thermal radiation light from the strip-like object so that, when the reference plane of the surface of the strip-like object is plane α, the angle φ between the orthogonal projection of the optical axis of the camera onto the plane α and the conveying direction p of the strip-like object is not 90 degrees, and an image processing step of calculating an index of the surface shape of the strip-like object based on the radiance of the strip-like object in the obtained image.

Description

[Technical field]

[0001] The present invention relates to a method for measuring the shape of a strip-like object, a method for controlling the shape of a strip-like object, a method for manufacturing a strip-like object, a method for quality control of a strip-like object, an apparatus for measuring the shape of a strip-like object, and a manufacturing facility for a strip-like object. [Background technology]

[0002] In the materials industry, shape management of strip materials is important, and quantification of product shapes has been required. For example, there is a high demand for measuring the shape of steel materials in the steelmaking process from the viewpoints of operational stability and product quality assurance. In particular, shape measurement during rolling to produce a product into the desired shape is important because it leads to improved product quality and operational stability by providing feedback for initial setting of rolling conditions and for rolling control during rolling.

[0003] For example, in a hot-rolled steel sheet manufacturing line, a rectangular semi-finished product called a slab, which is in a high-temperature state after being extracted from a heating furnace, is processed into a sheet through a sizing mill, rough rolling, and finish rolling, and then wound up into a coil to be manufactured. During this process, depending on the rolling conditions, the reduction in the width direction of the steel sheet may become uneven, causing partial elongation and resulting in defective shape.

[0004] For example, when only the edge portion (widthwise end portion) of a steel sheet is stretched compared to the center portion (widthwise center portion), the edge portion will have a wavy shape. Conversely, when only the center portion is stretched, the center portion will have a wavy shape. Such shape defects not only result in a defective product, but also deteriorate the sheet passing properties in the next process such as pickling and cold rolling, causing problems, so there is a strong demand to prevent shape defects.

[0005] In order to improve shape defects, it is necessary to appropriately set the load in the width direction during rolling. However, due to various disturbances such as wear of the rolling rolls, temperature distribution of the steel plate, and variations in material property distribution, it has been very difficult to obtain optimal rolling conditions by calculation alone. Therefore, in order to set optimal rolling conditions, it is essential to derive optimal initial settings by comparing measurements of the steel plate shape with a rolling model, and perform preset control or feedback control of the rolling conditions in real time. Only by performing such control can it become possible to suppress shape defects.

[0006] However, it is difficult to measure the shape of a steel sheet after it has been made into a rolled product, and since feedback control requires measurement during rolling production, it is preferable to measure the shape immediately after the finish rolling exit, which is the final rolling process. For example, when the elongation of the center of the steel sheet is significant compared to the edge of the steel sheet, bender control is performed to eliminate bias of elongation to the center while allowing elongation of the edge by adjusting the load balance in the width direction of the rolling roll. The shape described here mainly refers to the longitudinal sheet elongation that occurs locally in the width direction of the steel sheet during rolling, and specifically includes "elongation of the center" and "elongation of the edge".

[0007] As a technique for measuring the shape of a steel sheet immediately after the exit side of finish rolling, various techniques have been proposed in the past, such as a method using a rod-shaped light source or a magnetic sensor. Among these, Patent Documents 1 to 3, for example, disclose a particularly effective technique in which a point-like or linear light beam is irradiated onto a target surface using a laser, and the shape is measured by measuring the reflected light.

[0008] Furthermore, Patent Document 4 discloses a technology that uses three line lasers whose longitudinal direction is perpendicular to the conveying direction of the steel plate as a laser irradiation method. In the technology disclosed in Patent Document 4, a line laser is irradiated in parallel to the longitudinal direction of the steel plate so as to form three equally spaced lines, and the reflected images are acquired and the profiles of each laser are compared to remove the effects of vertical vibration of the steel plate.

[0009] Furthermore, Patent Documents 5 to 7 and Non-Patent Document 1 disclose a technology in which a powerful LED light source is used to project a stripe pattern consisting of multiple lines onto the target surface, thereby increasing the number of lines projected more cheaply than with a laser, thereby enabling stable shape measurement regardless of the specularity or tilt of the target.

[0010] The need for measuring the shape of steel sheets during manufacturing exists not only for hot-rolled steel sheets, but also for other strip-shaped material, regardless of whether it is in a red-hot state (e.g., 600°C or higher), a warm state (e.g., 300°C to 600°C), or a cold state (e.g., near room temperature). Note that the "strip" mentioned here refers to a long material. Strip-shaped objects include products that are ultimately wound into a roll, such as iron, paper, cloth, and non-ferrous metals such as aluminum, as well as products that are formed into rectangular plates, such as thick steel plates. [Prior art documents] [Patent documents]

[0011] [Patent Document 1] Japanese Unexamined Patent Publication No. 56-124006 [Patent Document 2] Japanese Patent Application Publication No. 55-40924 [Patent Document 3] Japanese Patent Publication No. 58-11708 [Patent Document 4] Japanese Patent Application Publication No. 61-40503 [Patent Document 5] JP 2008-58036 A [Patent Document 6] JP 2011-99821 A [Patent Document 7] JP 2016-65863 A [Non-patent literature]

[0012] [Non-Patent Document 1] Ise, et al., “Development of a hot-rolled steel sheet flatness meter using LED dot pattern projection method”, Iron and Steel, The Iron and Steel Institute of Japan, 2019, Vol. 105, No. 1, pp. 20-29 [Non-Patent Document 2] Kaneshige, “Heat Measurement by Radiation Thermometer”, Molding and Processing, Society of Plastics Processing, 2020, Vol. 32, No. 4, pp. 121-124 [Non-Patent Document 3] Inoue, "Research on non-contact temperature measurement method for metals in cold and hot rolling", Report of Grant-in-Aid for Scientific Research AF-1997014 Summary of the Invention [Problem to be solved by the invention]

[0013] The techniques disclosed in Patent Documents 1 to 7 are all methods for measuring the shape of a target by irradiating light onto a hot-rolled steel sheet using a light source and capturing the reflected light with a camera. However, considering the effects of high temperatures due to radiant heat, and the adhesion of steam, dust, oil, and the like to the steel sheet, for example, advanced technology is required to perform stable measurements over a long period of time with a light source or sensor placed close to the steel sheet during transportation, and maintenance costs are also high.

[0014] One way to prevent this is to move the light source away from the object, but this would result in a decrease in the amount of light due to diffusion, making it difficult to design an optical system that can stably collect light in order to ensure the amount of light. Another possibility is to use a magnetic sensor, but this requires that the sensor itself be brought close to the object being measured, which also makes installation and maintaining performance difficult.

[0015] The present invention has been made in consideration of the above, and aims to provide a method for measuring the shape of a strip-like object, a method for controlling the shape of a strip-like object, a method for manufacturing a strip-like object, a quality control method for a strip-like object, an apparatus for measuring the shape of a strip-like object, and manufacturing equipment for a strip-like object, which can be easily and stably operated without bringing a light source or sensor close to the object to be measured, and which also reduces maintenance costs, for parts other than the edge of the strip-like object. [Means for solving the problem]

[0016] (1) A shape measuring method of a belt-like object according to the present invention is a shape measuring method for measuring the shape of a belt-like object, comprising the steps of: When the reference plane of the surface of the belt-like object is a plane α, The angle φ between the orthogonal projection of the optical axis of the camera onto the plane α and the conveying direction p of the belt-like object is not 90 degrees. an imaging step of capturing an image of thermal radiation light from the belt-shaped object; an image processing step of calculating an index of a surface shape of the belt-like object based on the radiance of the belt-like object in the obtained image; It includes.

[0017] (2) The present invention also provides a method for measuring the shape of a belt-like object, comprising the steps of: The image processing step extracts linear components parallel to a transport direction of the belt-like object from the radiance of the belt-like object.

[0018] (3) A method for measuring the shape of a belt-like object according to the present invention is the method for measuring the shape of a belt-like object according to the above (1) or (2), further comprising the steps of: The imaging step is to set the angle θ between the plane α and the optical axis of the camera to 20 degrees or less.

[0019] (4) A method for measuring the shape of a belt-like object according to the present invention is the method for measuring the shape of a belt-like object according to any one of (1) to (3) above, further comprising: The image processing step calculates, from the obtained light and dark pattern of the band-like object, one or more of the steepness, wave height, wave pitch, elongation amount, and elongation rate at each position in the width direction of the surface of the band-like object as the index.

[0020] (5) Furthermore, the method for controlling the shape of a strip-like object according to the present invention measures the shape of the strip-like object using a method for measuring the shape of a strip-like object described in any one of (1) to (4) above, and controls the shape of the strip-like object to a desired shape based on the measurement results.

[0021] (6) Furthermore, the method for manufacturing a strip-shaped object of the present invention involves measuring the shape of the strip-shaped object using a method for measuring the shape of a strip-shaped object described in any one of (1) to (4) above, and manufacturing the strip-shaped object based on the measurement results.

[0022] (7) Furthermore, the quality control method for a strip-like object of the present invention measures the shape of the strip-like object using the shape measurement method for a strip-like object described in any one of (1) to (4) above, and controls the quality of the strip-like object based on the measurement results.

[0023] (8) A shape measuring device for a belt-like object according to the present invention is a shape measuring device for measuring the shape of a belt-like object, comprising: When the reference plane of the surface of the belt-like object is a plane α, The angle φ between the orthogonal projection of the optical axis of the camera onto the plane α and the conveying direction p of the belt-like object is not 90 degrees. an imaging means for capturing an image of thermal radiation light from the belt-shaped object; an image processing means for calculating an index of a surface shape of the belt-like object based on the radiance of the belt-like object in the obtained image; It is equipped with the following.

[0024] (9) Furthermore, a manufacturing facility for a belt-like object according to the present invention includes the shape measuring device for a belt-like object described above in (8). Effect of the Invention

[0025] The shape measurement method for a strip-like object, the shape control method for a strip-like object, the manufacturing method for a strip-like object, the quality control method for a strip-like object, the shape measurement device for a strip-like object, and the manufacturing equipment for a strip-like object according to the present invention can be easily and stably operated without bringing a light source or sensor close to the object to be measured, and maintenance costs can also be reduced. [Brief description of the drawings]

[0026] [Figure 1]FIG. 1 is a diagram showing a schematic configuration of an apparatus for measuring the shape of a belt-shaped object according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a diagram showing an example of a state in which a change in inclination due to sheet elongation is imaged as a light and dark pattern in a steel sheet immediately after hot finish rolling. [Diagram 3] FIG. 3 is a diagram showing an example of an experiment for investigating the angular characteristics of the emissivity of the surface of a steel plate. [Figure 4] FIG. 4 is a graph showing an example of the relationship between the radiance and the acceptance angle of the surface of a steel plate. [Diagram 5] FIG. 5 is a diagram for explaining the mechanism by which bright and dark patterns occur in a steel sheet. [Figure 6] FIG. 6 shows an example of a camera arrangement for capturing the elongation of a steel plate as a light and dark pattern, where (a) is a diagram showing the positional relationship viewed from an oblique angle, (b) is a diagram showing the positional relationship viewed from above, and (c) is a diagram showing the positional relationship viewed from the direction δn of (b). [Figure 7] FIG. 7 shows examples of images of a steel sheet when it is in a normal state and when it has a defective shape. [Figure 8] FIG. 8 is a flowchart showing a specific process flow of the image processing steps performed by the image processing device of the apparatus for measuring the shape of a belt-shaped object according to the embodiment of the present invention. [Figure 9] FIG. 9 is a diagram for explaining the binarization process in the image processing step of the method for measuring the shape of a band-shaped object according to the embodiment of the present invention. [Figure 10] FIG. 10 is a diagram for explaining the rotation process in the image processing step of the method for measuring the shape of a belt-shaped object according to the embodiment of the present invention. [Figure 11] FIG. 11 is a diagram for explaining the luminance profile extraction process in the image processing step of the method for measuring the shape of a band-shaped object according to the embodiment of the present invention. [Figure 12] FIG. 12 is a diagram showing the surface of a steel plate cut at a plane δ, where the normal n of the conveying table is the Y axis and the direction perpendicular to the Y axis within the plane δ is the X axis. [Figure 13]FIG. 13 is a graph showing an example of the relationship between the radiance and the acceptance angle of the surface of a steel plate. [Figure 14] FIG. 14 is a graph showing an example of the relationship between steepness and the rate of change in brightness. [Figure 15] FIG. 15 is a diagram showing an example of an image of a steel plate captured by a camera. [Figure 16] FIG. 16 is a diagram showing an example of a case where it is difficult to distinguish between the plate surface of a steel plate and a structure. [Figure 17] FIG. 17 is a diagram showing an example of processing using a low-pass filter that is performed when it is difficult to distinguish between the plate surface of a steel plate and a structure in a shape measuring method for a belt-shaped object according to an embodiment of the present invention. [Figure 18] FIG. 18 shows an example in which the apparatus for measuring the shape of a belt-shaped object according to an embodiment of the present invention is applied to determining whether or not the shape is acceptable. [Figure 19] FIG. 19 shows an example in which the apparatus for measuring the shape of a strip-like object according to an embodiment of the present invention is applied to rolling feedback control. [Figure 20] FIG. 20 shows an example in which the shape measuring device for a strip-shaped object according to the embodiment of the present invention is applied to rolling control using machine learning. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0027] A method for measuring the shape of a strip-like object, a method for controlling the shape of a strip-like object, a method for manufacturing a strip-like object, a quality control method for a strip-like object, a shape measuring device for a strip-like object, and a manufacturing facility for a strip-like object according to embodiments of the present invention will be described with reference to the drawings. Note that the components in the following embodiments include those that are replaceable and easy for a person skilled in the art, or those that are substantially the same.

[0028] (shape measuring device) A shape measuring device for a strip-like object according to an embodiment will be described with reference to Figs. 1 to 17. The shape measuring device is a device for measuring the shape of a strip-like object. Below, a case where the shape measuring device is applied to hot finish rolling will be described. Also, below, a case where the strip-like object to be measured is a steel plate will be described. Also, below, a case where the shape measured by the shape measuring device is the elongation of a portion other than the edge portion of the steel plate, specifically, the elongation of the central portion of the steel plate will be described.

[0029] 1, the shape measuring device according to the embodiment includes a camera 2 and an image processing device 3. First, the camera 2 will be described in detail.

[0030] As described below, the camera 2 is positioned so that the angle φ between the "orthogonal projection of the camera's optical axis onto the plane α" and the "transport direction p of the strip-like object (steel sheet S)" is not 90 degrees (see FIG. 6). Here, the plane α refers to the reference plane of the surface of the strip-like object. Then, using the camera 2 positioned in this way, an image of the thermal radiation light of the steel sheet S at the hot finish rolling exit side, which has been rolled by the rolling rolls 1, is captured.

[0031] If a commercially available digital camera or the like is used as the camera 2, problems such as blurring of the image or graininess occur, making it impossible to clearly capture the shape of the steel sheet S. Therefore, technical points (1) to (4) for accurately capturing the shape of the steel sheet S with the camera 2 will be described below.

[0032] (1) Ensuring sufficient light for imaging First, it is necessary to ensure the amount of light necessary to obtain a clear image. At the hot finishing rolling exit, the steel sheet S may pass through at a speed of 20 m / s or more, which is extremely fast. To capture a fast-moving object clearly and without blur, it is preferable to shorten the exposure time. For example, when capturing an image at 20 m / s with a resolution of about 2 mm and pixel blur of 1 pixel, i.e., within 2 mm, the allowable exposure time is only 0.1 ms, and the amount of light received, which is proportional to the exposure time, is also very small.

[0033] The temperature of the steel sheet at the hot finish rolling exit side is about 900°C. As shown in Fig. 5 of the above Non-Patent Document 2, the peak wavelength of thermal radiation light at about 900°C (1200K) is 2.5μm, and the sensitivity is low in the visible region (0.4 to 0.7μm). Therefore, it is preferable to use a camera 2 equipped with an imaging element such as InGaAs, PbS, or PbSe.

[0034] On the other hand, cameras using imaging elements such as InGaAs, PbS, PbSe, etc. are expensive, and the price increases depending on the resolution, so the introduction cost is high when trying to capture images with high resolution. Therefore, it is preferable to use a camera 2 equipped with an inexpensive Si imaging element and capable of using the near-infrared sensitivity region of 0.8 to 1.0 μm. By using such a camera 2, it is possible to obtain a sufficient amount of thermal radiation light at a low cost.

[0035] In addition, when applying this method to a lower temperature object, it is preferable to use a camera 2 equipped with an imaging element having sensitivity on the longer wavelength side. For example, when the measurement object is about 400°C, if the introduction cost is not considered, a camera 2 equipped with an InGaAs imaging element having sensitivity at 1.2 to 1.7 μm can be used. In addition, when the measurement object is about 200°C, a camera 2 equipped with an imaging element such as PbS or PbSe having sensitivity at 3 to 5 μm can be used. This makes it possible to ensure a sufficient amount of light. In this way, it is preferable to select a camera 2 equipped with an imaging element having sensitivity in an appropriate wavelength band depending on the transport speed, resolution, temperature, and depth of field described later of the measurement object.

[0036] (2) Positional relationship between the steel plate and the camera Secondly, in order to clearly capture the shape of the steel plate S, the positional relationship between the steel plate S to be measured and the camera 2 is considered. Here, we focus on the slight change in tilt in the longitudinal direction caused by elongation that appears on the plate surface when elongation occurs (especially elongation of parts other than the edges of the strip-like object, especially the central part), and consider capturing an image of the change in tilt using thermal radiation light caused by heating.

[0037] The inventors obtained knowledge by repeatedly imaging red-hot steel sheet S under various optical conditions, and also conducted laboratory heating imaging tests. As a result, they discovered that by imaging the steel sheet S with a low angle (light receiving angle) between the reference plane of the surface of the steel sheet S and the optical axis of the camera 2, it is possible to capture slight inclinations on the surface of the steel sheet S as changes in brightness in the image. For example, Figure 2 shows how the inclination changes due to sheet elongation are imaged as light and dark patterns in the red-hot steel sheet S immediately after hot finish rolling.

[0038] FIG. 3 shows an experiment in which the angular characteristics of the emissivity of the surface of a steel sheet S were investigated. In the shape measuring device according to the embodiment, the thermal radiation light caused by heating the steel sheet S to be measured is imaged, so that the heating process was simulated using the device in FIG. 3. Therefore, as shown in FIG. 3, a small cut steel sheet sample SA was placed on a heater 4 and imaged by a camera 2. In addition, a tilt mechanism 5 was used that can reduce the angle (light receiving angle) between the reference plane of the surface of the steel sheet sample SA and the optical axis of the camera 2 while keeping the surface of the steel sheet sample SA to be measured in the field of view. As a result, the thermal radiation light caused by heating the steel sheet sample SA was stably imaged at an arbitrary light receiving angle θ (vertical is defined as 90 degrees) while the steel sheet sample SA was heated by the heater 4.

[0039] Using the device shown in Figure 3, images of thermal radiation caused by heating steel plate sample SA were repeatedly taken at each acceptance angle θ, and the relationship between radiance and acceptance angle θ was investigated. The obtained relationship between radiance and acceptance angle θ is shown in Figure 4. In Figure 4, the vertical axis is radiance, and the horizontal axis is acceptance angle θ. Furthermore, radiance was normalized so that 100 was the maximum. Furthermore, since radiance and emissivity are in a proportional relationship, radiance may hereafter be referred to as emissivity.

[0040] As shown in Fig. 4, the emissivity is constant from directly above the steel plate sample SA (beam-receiving angle θ = 90 degrees) to around 60 degrees, but thereafter the emissivity drops sharply as the beam-receiving angle θ becomes smaller. The mechanism by which the bright and dark patterns occur, which was considered based on the data in Fig. 4, will be explained with reference to Fig. 5.

[0041] When an image is taken with a low light-receiving angle θ, if elongation occurs in the longitudinal direction of the steel sheet S, a slight change in inclination occurs on the surface according to the shape of the elongation. As shown in Figure 5(a) at the front side of the ridge, the optical axis of camera 2 rises, so the light-receiving angle θ becomes large. On the other hand, as shown in Figure 5(b) at the back side of the ridge, the optical axis of camera 2 falls flat, so the light-receiving angle θ becomes small.

[0042] According to the data on the angular dependence of the emissivity of thermal radiation light due to heating shown in Figure 4, at low angles (for example, less than 0 degrees to 60 degrees), the radiance increases as the receiving angle θ increases, and the radiance decreases as the receiving angle θ decreases. Therefore, when the steel plate S is imaged by the camera 2, a light and dark pattern is formed on the image.

[0043] As described in Non-Patent Document 3, the angular dependence of the emissivity of thermal radiation due to heating can be theoretically explained by the complex refractive index of the object, but the model described in Non-Patent Document 3 has an issue in that it does not take into account surface roughness, coatings, etc. Note that this phenomenon is not limited to steel sheet S, but occurs similarly in strip-shaped objects made of various metallic and non-metallic materials, so it is possible to accurately capture slight tilt variations in strip-shaped objects other than steel sheet S.

[0044] Furthermore, the angular dependency of the emissivity of thermal radiation light due to heating does not depend much on the wavelength of the received light. Therefore, it is preferable to select the camera 2 according to the temperature of the steel plate S to be measured. When selecting the camera 2, it is preferable to consider whether the imaging element of the selected camera 2 can capture an image of a wavelength that can ensure a sufficient amount of light for the temperature and a wavelength with little disturbance. There is also a correlation between the intensity of the light-dark pattern and the amount of change in the slope, and as described later, it is possible to index the degree of plate elongation (especially elongation of parts other than the edge parts of the strip-shaped object, especially the central part).

[0045] Next, based on the above mechanism, we will consider the optical conditions under which the light and dark pattern can be observed with high accuracy. An example of the arrangement of the camera 2 for capturing the plate elongation as a light and dark pattern is shown in Figure 6. In Figure 6, (a) is a diagram of the positional relationship seen from an oblique angle, (b) is a diagram of the positional relationship seen from above, and (c) is a diagram of the positional relationship seen from the direction δ in (b). n Here, the view is taken from the direction δ n is the direction in which the optical axis of the camera 2 can be seen from the side. n By defining the above equation, the magnitude of the light-receiving angle θ, which will be described later, can be seen accurately.

[0046] In (a), (b), and (c) of Fig. 6, a plane parallel to the conveying table of the steel sheet S is denoted as α, and a plane including the conveying direction p of the steel sheet S and the normal n of the conveying table is denoted as β. Furthermore, the angle between the optical axis of the camera 2 and the plane α is denoted as θ (light-receiving angle θ), and the angle between the orthogonal projection of the optical axis of the camera 2 onto the plane α and the conveying direction p is denoted as φ. The plane α includes the surface of the belt-like object (steel sheet S) when the belt-like object (steel sheet S) is conveyed stably in a substantially flat shape. Therefore, the plane α is the same plane as the reference plane in Fig. 3 and is the reference plane of the surface of the belt-like object (steel sheet S).

[0047] The direction of the normal n of the conveying table is the same as the normal direction of the surface of the steel sheet S when the steel sheet S is stably conveyed in a substantially flat shape. Therefore, the plane α includes the conveying direction p of the belt-like object (steel sheet S) and is perpendicular to the normal direction of the surface of the belt-like object (steel sheet S). The plane β also includes the conveying direction p of the belt-like object (steel sheet S) and the normal direction of the surface of the belt-like object (steel sheet S). In FIG. 6, the intersection of the plane α and the optical axis is defined as point 0. The plane perpendicular to the conveying direction of the steel sheet is defined as plane γ. In other words, the closer the angle φ is to 90 degrees, the closer the plane γ is to being parallel to the optical axis.

[0048] First, the acceptance angle θ, which is the angle between the plane α of the reference surface of the surface of the steel sheet S and the optical axis of the camera 2, is set. The acceptance angle θ may be set appropriately depending on the purpose and location of the shape measurement. For example, as described above, it may be set based on the relationship between the thermal radiation light due to heating obtained through experiments and the acceptance angle θ. When using the experimental results of Figure 4, it is desirable to set the acceptance angle θ, which is the angle between the plane α of the reference surface of the surface of the steel sheet S and the optical axis of the camera 2, to 20 degrees or less.

[0049] The inclination of the surface of the steel sheet S due to sheet elongation occurs in the longitudinal direction of the steel sheet S, i.e., in a direction parallel to the conveying direction p. Therefore, even if an image is captured so that the optical axis of the camera 2 is perpendicular to the conveying direction of the steel sheet S, i.e., in a direction where the angle φ is 90 degrees, it is very difficult to capture the variation in inclination as a light and dark pattern. Therefore, the optical axis of the camera 2 is positioned so that the angle φ is not 90 degrees.

[0050] Furthermore, it is desirable that the angle φ is 45 degrees or less. It is most preferable that the angle φ is 0 degrees. However, by bringing the angle φ closer to 0 degrees, the camera installation position will be closer to the transfer line, which will cause the installation environment to deteriorate, such as high temperatures due to radiant heat. Therefore, engineering is required to ensure stable operation even in adverse environments, so the angle φ may be as small as possible while keeping the camera away from the transfer line to a degree that is not affected by thermal radiation, etc.

[0051] The condition under which the light and dark pattern of sheet elongation (especially elongation of parts other than the edges of the strip, and especially elongation of the central part) is most emphasized is to capture images from the same direction as the conveying direction of the steel sheet S or from the opposite direction. However, in this case, it is necessary to install the camera 2 directly above the line or near the line, which is not preferable because it means that the camera is installed in a bad environment containing mist, dust, high temperatures, etc.

[0052] Furthermore, by capturing an image of the steel sheet S at a low angle relative to the light receiving angle θ as shown in Figure 6, the distance between both ends of the steel sheet S in the image becomes smaller, making it possible to capture images of both edges in a smaller field of view. In addition, a smaller field of view also results in a smaller image size, which is advantageous when the transport speed of the steel sheet S to be measured is high and high-speed imaging and image processing are required.

[0053] (3) Distance between the steel plate and the camera Thirdly, the distance between the steel sheet S to be measured and the camera 2 is increased. The reason for this is that by placing the camera 2 as far away as possible from the production line, it is possible to install it in a good environment and to reduce the difference in optical conditions such as the light receiving angle θ and the angle φ in the width direction of the steel sheet S, i.e., at both edges. If there is a difference in optical conditions in the width direction of the steel sheet S, it will appear as a difference in appearance. Therefore, when judging by visual inspection, there is a risk of misjudging the degree of shape defect, and when quantifying the degree of shape defect by image processing, a larger correction is required. To increase the distance, it is preferable to use a telephoto lens when capturing the image. By using a telephoto lens, the difference in optical conditions can be reduced.

[0054] (4) Setting the correct aperture Fourth, to ensure the depth of field, the aperture value of the camera 2 is appropriately set. For example, assume that an image is to be captured of the entire surface of the steel plate S, including both the front (lower) and rear (upper) edge portions. In this case, if the width of the steel plate S is d (mm), the difference ΔL (mm) between the distance from the camera 2 to the front edge portion and the distance from the camera 2 to the rear edge portion can be expressed by the following formula (1).

[0055] ΔL = dcosθ / sinφ (1)

[0056] To obtain an image in focus on both edges of the steel sheet S, a depth of field (range in focus) of at least ΔLd (mm) is required. Since the greater the aperture value, the greater the depth of field, it is preferable to set the aperture to ΔLd (mm) or more. However, if the aperture value is increased, the amount of light will be insufficient, and there is a concern that blurring will occur. Therefore, it is preferable to determine the aperture value and focal length that can achieve both blurring and depth of field depending on the conveying speed of the steel sheet S to be measured and the required resolution. Next, the image processing device 3 will be described.

[0057] The image processing device 3 is realized by, for example, a general-purpose computer such as a workstation or a personal computer. The image processing device 3 may be installed near the camera 2, or may be installed on the cloud if high speed is not required.

[0058] As described later, the image processing device 3 calculates an index of the surface shape of the steel sheet S based on the radiance of the steel sheet S in the image captured by the camera 2. Furthermore, as described later, the image processing device 3 appropriately selects one or more of the steepness, wave height, wave pitch, elongation amount, and elongation rate at each position in the width direction of the surface of the steel sheet S from the light and dark pattern of the steel sheet S, and calculates them as the above indexes. Below, a process of calculating an index of the shape of the steel sheet S from the image obtained by the camera 2 using the image processing device 3 will be described.

[0059] Fig. 7(a) shows an image of the steel sheet S under normal conditions, and Fig. 7(b) shows an image of the steel sheet S when a shape defect has occurred. As shown in Fig. 7, the state of sheet elongation can be determined visually. The image processing device 3 calculates an index of the shape of the steel sheet S from the acquired image of the steel sheet S, for example, by the procedure shown in Fig. 8. In the following, for the sake of convenience of explanation, the axis that is closer to being parallel to the conveying direction of the steel sheet S is taken as the horizontal axis with respect to the vertical and horizontal axes of the image.

[0060] First, as shown in Fig. 9, only the plate region of the steel plate S is extracted by binarization processing (step S1 in Fig. 8). Fig. 9(a) is an image before binarization processing, and Fig. 9(b) is an image after binarization processing.

[0061] At this time, disturbances may occur, such as water riding on the plate surface or splashes of cooling water causing localized reductions in brightness on the plate surface, or splashes of water in the space above the plate scattering the thermal radiation light from the steel plate S and causing it to shine brightly. Since these disturbances are often very small and in the high frequency range relative to the pitch of the shape to be calculated, it is desirable to carry out expansion / contraction processing or removal of connected and isolated points by a median filter or the like on the plate region extracted in the binarization processing step (step S2 in Fig. 8).

[0062] Furthermore, after removing connected and isolated points, multiple blobs (lumps recognized by connecting surrounding pixels during binarization) that are candidates for plate regions may be generated. In this case, the plate region may be determined by extracting the blobs (step S3 in FIG. 8) or by determining whether or not it is a plate region based on the size, orientation, etc. of the steel plate S.

[0063] Next, for the plate region of the steel plate S obtained as described above, a light and dark pattern occurring perpendicular to the conveying direction of the steel plate S is extracted. Specifically, the extraction of the light and dark pattern refers to the calculation of a luminance profile. In this case, in order to make it easier to extract the light and dark pattern, the image is rotated so that the conveying direction of the steel plate S coincides with the vertical axis or horizontal axis of the image (step S4 in FIG. 8), for example, as shown in FIG. 10. (a) in FIG. 10 shows the image before rotation, and (b) in FIG. 10 shows the image after rotation.

[0064] At this time, it is necessary to determine the conveying direction of the steel sheet S. As long as the field of view of the camera 2 does not change, the conveying direction may be a fixed direction in advance, or may be automatically calculated from the image. For example, the upper and lower contours of the plate area may be fitted with straight lines, and the average of the inclinations may be calculated to determine the conveying direction of the steel sheet S. In addition, when the plate area is relatively long in the longitudinal direction, an elliptical approximation may be performed on the blob of the plate area, and the direction of the obtained major axis may be determined as the conveying direction. Similar results can also be obtained by calculating the direction in which the Feret's diameter is maximum for the above-mentioned blob.

[0065] Next, the positions of the upper and lower edges are extracted, with the up-down direction of the obtained image being the plate width direction (step S5 in FIG. 8).

[0066] Next, a luminance profile at a predetermined position in the width direction of the steel sheet S is calculated (step S6 in FIG. 8). In this step, as shown in FIG. 11, for example, the luminance profile is calculated by extracting linear components parallel to the conveying direction of the steel sheet S from the radiance of the steel sheet S. FIG. 11(a) is an image before the luminance profile is calculated, and FIG. 11(b) is the calculated luminance profile. Note that in this embodiment, the conveying direction p of the steel sheet S coincides with the rolling direction of the steel sheet S.

[0067] In this step, first, the coordinates of the upper and lower edge parts of the steel sheet S are calculated, and then the coordinate in the width direction for calculating the luminance profile is calculated from the relative position of these two coordinates. For example, if the coordinate of the upper edge part of the steel sheet S is y1 and the coordinate of the lower edge part is y2, the coordinate of the width direction center (sheet center) can be calculated by "(y1+y2) / 2". This makes it possible to extract, from the radiance of the steel sheet S, a linear component parallel to the conveying direction of the steel sheet S at the width direction center of the steel sheet S.

[0068] Furthermore, when calculating the luminance profile at a position α% from the upper edge of the steel sheet S, the coordinates of the corresponding location can be calculated by (1-α)y1+αy2). This makes it possible to extract, from the radiance of the steel sheet S, a linear component parallel to the conveying direction of the steel sheet S at a specific position in the width direction of the steel sheet S.

[0069] When calculating the luminance profile at a predetermined position in the width direction of the steel sheet S, local noise may be added due to water droplets, etc. Therefore, the influence of noise may be reduced by extracting not only the luminance profile of one line at a predetermined position in the width direction of the steel sheet S, but also the luminance profiles of several lines above and below it, and averaging them in the vertical direction of the image.

[0070] Next, an index of the shape of the steel sheet S is calculated from the obtained brightness profile (step S7 in Fig. 8). As shown in Fig. 6 described above, when the surface of the steel sheet S is imaged from a low angle with respect to the steel sheet S and from a direction oblique to the conveying direction of the steel sheet S, a bright and dark pattern occurs according to the change in inclination caused by the shape, and the intensity of the bright and dark pattern increases as the change in inclination increases. Therefore, by indexing the intensity of the bright and dark pattern caused by the shape, it becomes possible to index the degree of sheet elongation at a specific position in the width direction of the steel sheet S.

[0071] In addition, the wave pitch of the waves generated by the shape of the steel sheet S depends on the diameter of the rolling roll 1 and is within a certain range. Therefore, by performing frequency analysis and extracting only the frequency components caused by the sheet elongation, it becomes possible to reduce high-period or fixed-period noise. The frequency analysis may use a low-pass filter such as a moving average filter, or may use a Fourier transform, an inverse Fourier transform, or the like. In addition, as the high-pass filter, a frequency filter similar to the low-pass filter may be used, or a difference may be taken after a polynomial approximation, such as taking the difference after a linear approximation, and the difference between the zeroth-order and first-order components may be taken. In this way, an index of the shape of the steel sheet S is calculated from the brightness profile from which only the components of the sheet elongation are extracted.

[0072] The method for calculating the index of the shape of the steel sheet S may be various methods that can quantify the intensity of the light and dark pattern, and the following methods (i) to (iii) can be used, for example. (i) The difference or ratio between maximum and minimum luminance is extracted and used as an index. The method for calculating maximum and minimum luminance does not necessarily have to be the maximum and minimum values, but percentiles, such as sorting the corresponding range in descending order and extracting the top 10%, can also be used. (ii) The average value of the luminance profile is corrected to 0, and the variance and standard deviation are used as indices. (iii) The relationship between the intensity of the light and dark pattern (maximum value, minimum value, standard deviation) and the shape indices (steepness and elongation) is experimentally or theoretically linked to create a table or conversion formula, which is then applied during actual measurement to calculate the shape indices of steel sheet S.

[0073] Furthermore, in the shape index (i) above, by considering the relationship between the angular characteristics of emissivity and the change in inclination of the surface of the steel sheet S (hereinafter referred to as the "steel sheet surface") caused by sheet elongation (especially the elongation of the parts other than the edge parts of the strip-like object, especially the elongation of the central part), it is also possible to calculate the steepness from the light-dark pattern based on physical theory.

[0074] First, we formulate the relationship between the steepness and the change in the inclination of the optical axis direction of the camera 2 on the steel plate surface (hereinafter referred to as the "camera optical axis direction"). As a premise, the plate elongation is a sine wave, with an amplitude of h / 2 and a period of L. The steepness λ at this time is h / L.

[0075] Here, in order to consider the inclination variation of the plate surface in the direction of the camera's optical axis, a plane δ is assumed to be formed by the normal n of the conveying table and the optical axis. If the normal n of the conveying table is defined as the Y axis, and the direction perpendicular to the Y axis within plane δ (parallel to plane δ) is defined as the X axis, the steel plate surface is cut at plane δ as shown in Figure 12, and is expressed by the following formula (2). Note that the origin in Figure 12 is set to the midpoint of the steel plate in the width direction.

[0076] In this case, if the front edge of the steel sheet S with respect to the camera 2 is S1 and the rear edge is S2, the surface of the steel sheet S cut at the plane δ becomes the line segment S1S2, as shown in FIG. 6(b). This line segment S1S2 becomes a sine wave with a period of L / cosφ and its phase is ψ. More specifically, the front edge S1 is a point that represents the edge on the camera 2 side of the line segment formed by the plane δ and the steel sheet surface. The rear edge S2 is a point that represents the edge on the opposite side to the camera 2 of the line segment formed by the plane δ and the steel sheet surface.

[0077]

number

[0078] In the above formula (2), Y is the normal n of the conveyor table, X is the direction perpendicular to the Y axis within the plane δ, h / 2 is the amplitude, L is the period, and ψ is an arbitrary phase.

[0079] Next, we consider the relationship between the inclination toward the camera optical axis and brightness. As shown in Figure 4, in low-angle imaging, the radiance increases as the receiving angle increases. When the receiving angle θ of the line segment S1S2 with respect to the camera optical axis direction is the largest, that is, when the inclination of the above formula (2) is maximum, the image becomes the brightest. The inclination at this time is ω2. This ω2 is the maximum inclination of the line segment S1S2. Similarly, when the receiving angle θ of the line segment S1S2 with respect to the camera optical axis direction is the smallest, that is, when the inclination of the above formula (2) is the smallest, the image becomes the darkest. The inclination at this time is ω1. This ω1 is the minimum inclination of the line segment S1S2.

[0080] In order to find the maximum gradient ω2 and the minimum gradient ω1, the above formula (2) is differentiated with respect to X to obtain the following formula (3).

[0081]

number

[0082] From the obtained above formula (3), the maximum slope ω2 can be obtained as in the following formula (4), and the minimum slope ω1 can be obtained as in the following formula (5). Also, as shown in the following formulas (4) and (5), the absolute values of the maximum slope ω2 and the minimum slope ω1 are the same value.

[0083]

Number

Number

[0084] Let the angle formed by the tangent line of the maximum slope ω2 at this time and the X-axis, and the angle formed by the tangent line of the minimum slope ω1 and the X-axis be Δθ (degrees) respectively (see Figure 12). Then, replacing h / L with the steepness λ and using the approximation with h << L, the relationship between Δθ and the steepness λ can be expressed as in the following formula (6). Note that Δθ in the following formula (6) is, as shown in Figure 12, the angle formed by the reference plane (plane α) and the tangent line of the maximum slope ω2, and the angle formed by the reference plane (plane α) and the tangent line of the minimum slope ω1.

[0085]

Number

[0086] Next, from the angular characteristics of the emissivity shown in Figure 4, calculate the amount of brightness variation when the maximum light-receiving angle is θ + Δθ and when the minimum light-receiving angle is θ - Δθ. At this time, in order to cancel the influence of the brightness variation of the base caused by temperature changes, etc. of the object, calculate the luminance ratio of the bright part and the dark part, and if the relationship between the brightness change rate r and the steepness λ can be sorted out as the brightness change rate r, it becomes possible to calculate the steepness λ from the image. Note that the brightness change rate r may be obtained by automatically calculating the luminance of the bright part and the dark part from the image using image processing.

[0087] First, a formula is fitted to model the range of acceptance angle θ: 20 degrees or less, which is the range in which radiance I(θ) increases as the acceptance angle θ increases in the graph of Figure 4. Any formula can be used for fitting, but here we used a linear approximation as shown in formula (7) below. I(θ) in formula (7) below is a linear approximation of the 0<θ<20 region of the emissivity angular characteristics.

[0088]

number

[0089] Next, the light / dark change rate r is defined. The ratio of the radiance at the maximum light-receiving angle θ+Δθ, at which the radiance is greatest on the steel sheet surface, to the radiance at the minimum light-receiving angle θ-Δθ, at which the radiance is least, can be expressed by the following formula (8). However, θ in the following formula (8) is limited to the case where it is greater than Δθ.

[0090]

number

[0091] Finally, by expressing the steepness λ in terms of the rate of change in brightness r from the above equations (7) and (8), the following equation (9) can be obtained.

[0092]

number

[0093] In the above formula (9), the light-receiving angles θ and φ with respect to the reference plane (plane α) are values ​​that are determined in advance based on the installation position of the camera 2 with respect to the steel plate S, and the parameters a and b are determined from the angle dependency of the radiance. Therefore, it is possible to physically estimate the steepness λ by calculating the luminance values ​​of the bright and dark areas through image processing and substituting the ratio of these values ​​into the above formula (9) as the light-dark change rate r.

[0094] An example of estimating the steepness λ based on an actual light-dark pattern generated on an image of a steel sheet S is shown below. The camera 2 was installed on the steel sheet S so that the light-receiving angle θ with respect to the reference surface (plane α) was 12.5 degrees and the angle φ was 45 degrees. Then, by fitting the above formula (7) based on the angular characteristics of emissivity shown in Fig. 13, a = 3.5 and b = 20 were calculated. The straight line I(θ) in Fig. 13 is the straight line obtained as a result of the fitting. The graph obtained by substituting the obtained parameters a and b into the above formula (9) is shown in Fig. 14. By inputting the light-dark change rate r (the black circle on the right in Fig. 14) based on this graph, the steepness λ (the black circle on the left in Fig. 14) can be calculated.

[0095] Next, the image obtained by the camera 2 is shown in Fig. 15. A light-dark pattern was generated, and the light area luminance value was calculated to be 140 and the dark area luminance value was calculated to be 115 by image processing. Furthermore, by taking the ratio of these values, the light-dark change rate r was calculated to be 1.22, and by substituting this into the above formula (9), the steepness λ was successfully estimated to be 0.014. In the graph of Fig. 14, the point on the vertical axis (steepness λ) corresponding to the light-dark change rate r of 1.22 is also 0.014, and it is possible to calculate it from the graph of Fig. 14.

[0096] Strictly speaking, the distance from the camera 2 differs greatly between the upper edge and the lower edge, so the actual magnification and conveyance direction differ between the upper and lower parts of the plate area on the image, and these differences become more pronounced the closer the steel plate S to be measured is to the camera 2. Therefore, more strictly, it is desirable to perform keystone correction on the image using linear transformation or the like based on the camera parameters calculated in advance and the positional relationship of the measurement target. Also, by ensuring a sufficient distance between the steel plate S to be measured and the camera 2, the difference in imaging conditions within the field of view can be reduced.

[0097] Furthermore, in step S4 above, the image is rotated to facilitate extraction of the light and dark pattern, but a luminance profile may be extracted obliquely with respect to the conveyance direction of the steel sheet S without using the rotation process.

[0098] In the binarization process in step S1, the brightness of the thermal radiation light varies depending on the temperature of the object to be measured. Therefore, if the binarization process is performed with a fixed value, when the steel sheet S is bright, part of the background will be detected as the sheet area, and conversely, when the steel sheet S is dark, the background cannot be detected.

[0099] To address such issues, it is desirable to carry out luminance correction. For example, a method of luminance correction is to multiply the luminance of the entire image by a fixed value so that a representative value such as the maximum value, average value, median value, percentile value, etc. of the luminance of the entire image becomes a target value. Dark current correction may also be performed before the multiplication.

[0100] Also, as shown in Figure 16, for example, there are cases where the thermal radiation light emitted from the steel sheet S is irradiated onto structures such as transport rolls and tables, causing the structures to appear bright in the image, making it difficult to distinguish them from the sheet surface. In this case, the sheet surface appears bright in the image because it directly receives the thermal radiation light, but the structures are often darker than the sheet surface because they are reflections of the thermal radiation light emitted from the sheet surface.

[0101] Therefore, the binarization threshold value that can separate the structure from the plate by performing the above-mentioned brightness correction may be determined as a fixed value, but more stable detection is possible by automatically detecting the valley portion from the shape of the histogram of the entire image. When detecting the valley portion, for example, by applying a low-pass filter to the brightness histogram itself, it becomes possible to stably calculate the minimum value by differentiation processing, search processing, etc. FIG. 17(a) is an example of a brightness histogram, and is a graph with brightness on the horizontal axis and the number of pixels N on the vertical axis. FIG. 17(b) is an example of applying a low-pass filter to the brightness direction of the brightness histogram. Note that there are two valley portions in the histogram, one at the boundary between the plate surface portion and the structure, and the other at the boundary between the structure and the background, so it is preferable to select the larger of the two valleys. The portion divided by the dotted line in FIG. 17(b) corresponds to the binarization threshold value.

[0102] In addition, in this embodiment, an example has been described in which the image from the camera 2 is processed by the image processing device 3 to calculate an index of the shape of the steel sheet S, but the obtained camera image may simply be presented to the worker as it is and fed back to the rolling control.

[0103] Also, a classifier using machine learning may be used to estimate the shape index of the steel sheet S from an image. Specifically, first, a shape index measured by visual inspection or some other method is linked as a correct answer to an obtained image of the steel sheet S to create learning data. Then, using the created learning data and a machine learning method, a classifier is generated that takes an image as input and outputs a shape index, and this classifier is used to calculate the shape index of the target steel sheet S. Also, input data to the machine learning and classifier may be features calculated from an image, in addition to images. Also, there is no restriction on the machine learning method, but if real-time performance is not required, a convolutional neural network or the like may be used.

[0104] (Example of application to shape pass / fail judgment) An example in which the shape measuring device for a belt-shaped object according to the embodiment is applied to shape pass / fail judgment will be described with reference to Fig. 18. The pass / fail judgment system in Fig. 18 includes a camera 2, an image processing device 3, and a pass / fail judgment device 6.

[0105] First, the image processing device 3 calculates an index (shape data) of the shape of the steel sheet S from the image captured by the camera 2, and transmits it to the pass / fail determination device 6. The pass / fail determination device 6 determines whether the shape is pass / fail based on the steel sheet information (e.g., plate thickness, plate width, steel type, temperature, etc.) acquired from the upper system and the index of the shape of the steel sheet S. The pass / fail determination result is transmitted to the upper system. Based on the pass / fail determination result, the upper system determines whether correction is necessary, whether to cut off any parts with defective shape, whether rolling can be performed in the next process, etc. In this way, by utilizing the index of the shape of the steel sheet S in the action of the next process, it is possible to contribute to preventing trouble and improving product quality.

[0106] (Example of application to rolling feedback control) An example in which the shape measuring device for a strip-like object according to the embodiment is applied to rolling feedback control will be described with reference to Fig. 19. The rolling control system in Fig. 19 includes a camera 2, an image processing device 3, and a rolling control device 7.

[0107] First, the image processing device 3 calculates an index of the shape of the steel sheet S from the image captured by the camera 2, and transmits the calculated index to the rolling control device 7. The rolling control device 7 calculates control parameters using the index of the shape based on the steel sheet information (e.g., sheet thickness, sheet width, steel type, temperature, etc.) acquired from the upper system, other measurement data such as the sheet passing position, and the index of the shape of the steel sheet S. The rolling control device 7 also performs feedback control such as leveling by transmitting a control signal to the rolling rolls 1. By performing such feedback control, the shape of the product can be stabilized, and shape defects themselves can be reduced.

[0108] (Application of machine learning to rolling control) An example in which the shape measuring device for a strip-like object according to the embodiment is applied to rolling control using machine learning will be described with reference to Fig. 20. The rolling control system in Fig. 20 includes a camera 2, an image processing device 3, a rolling control device 7, a data server 8, a machine learning device 9, and a control parameter estimation device 10.

[0109] First, the image processing device 3 calculates an index of the shape of the steel sheet S from the image captured by the camera 2, and transmits it to the data server 8. The data server 8 accumulates the index of the shape linked to the steel sheet information (e.g., sheet thickness, sheet width, steel type, temperature, etc.) acquired from the upper system and the control parameters during rolling.

[0110] These accumulated data are transmitted to a machine learning device 9. The machine learning device 9 constructs a model by machine learning to estimate control parameters for rolling while suppressing shape defects. The estimated model is transmitted to a control parameter estimation device 10, which estimates control parameters based on the steel plate information acquired from a higher-level system. The control parameters are transmitted to a rolling control device 7. The rolling control device 7 performs preset control such as leveling by transmitting a control signal to the rolling rolls 1. By performing such preset control, the shape of the product can be stabilized and shape defects themselves can be reduced.

[0111] In this application example, the control parameters in the preset control have been described, but machine learning may also be applied to calculate the control parameters in the feedback control. In addition, by combining the preset control and the feedback control, it is possible to further improve the shape quality of the product.

[0112] In addition to the above application examples, the device for measuring the shape of a belt-like object according to the embodiment can be provided as part of a manufacturing facility for belt-like objects.

[0113] The method for measuring the shape of a strip-like object according to the embodiment may also be applied to a method for controlling the shape of a strip-like object, in which the shape of the strip-like object is measured by the method for measuring the shape of a strip-like object, and the shape of the strip-like object is controlled to a desired shape based on the measurement result.

[0114] The method for measuring the shape of a web-like object according to the embodiment may also be applied to a method for manufacturing a web-like object, in which the shape of the web-like object is measured by the method for measuring the shape of a web-like object, and the web-like object is manufactured based on the measurement results.

[0115] The method for measuring the shape of a strip-like object according to the embodiment may also be applied to a method for controlling the quality of a strip-like object, in which the shape of the strip-like object is measured by the method for measuring the shape of a strip-like object, and the quality of the strip-like object is controlled based on the measurement result.

[0116] The method for measuring the shape of a strip-like object, the method for controlling the shape of a strip-like object, the method for manufacturing a strip-like object, the quality control method for a strip-like object, the device for measuring the shape of a strip-like object, and the manufacturing equipment for a strip-like object according to the above-described embodiments provide the following effects.

[0117] First, by passively capturing images of the thermal radiation light from the steel sheet S being measured, it is possible to capture images from a distance and in a good installation environment without having to install light sources or sensors around the steel sheet S while it is being passed, and the shape of the steel sheet S can be clearly captured.

[0118] In addition, by selecting an imaging element suitable for the temperature of the target as the imaging element of the camera 2, it is possible to efficiently receive thermal radiation light. For example, for a measurement target of about 900°C, sensitivity can be increased by using the near-infrared components of a Si imaging element, and clear, blur-free images can be obtained by shortening the exposure time, even for steel plates S transported at high speed.

[0119] Furthermore, by capturing an image so that the angle φ between the orthogonal projection of the optical axis of the camera 2 onto the reference plane (plane α) and the conveying direction p of the steel sheet S is not 90 degrees, it is possible to clearly capture the sheet elongation that occurs on the surface of the steel sheet S at each position in the width direction. Here, a greater effect can be obtained if the light-receiving angle θ with respect to the reference plane (plane α) of the surface of the steel sheet S is set to 20 degrees or less.

[0120] In addition, the present invention has been described with respect to the steel plate S at the finish rolling exit side of the hot rolling process, but it goes without saying that the present invention can also be applied to other high-temperature plate-shaped steel materials such as thick steel plates and slabs. It goes without saying that the present invention can be applied to various strip-shaped objects made of different materials, not just strip-shaped objects in steelmaking processes, as long as the thermal radiation light of the object to be measured can be obtained. In addition, the present invention is preferable because it provides greater effects when the elongation of a portion other than the edge portion of the strip-shaped object is the object of shape measurement. In particular, it is more preferable because it provides even greater effects when the elongation of the center portion of the strip-shaped object is the object of shape measurement.

[0121] The method for measuring the shape of a strip-like object, the method for controlling the shape of a strip-like object, the method for manufacturing a strip-like object, the method for quality control of a strip-like object, the shape measuring device for a strip-like object, and the manufacturing equipment for a strip-like object according to the present invention have been specifically described above using the embodiments and examples for carrying out the invention, but the gist of the present invention is not limited to these descriptions and should be broadly interpreted based on the claims. Furthermore, it goes without saying that various changes and modifications based on these descriptions are also included in the gist of the present invention. [Explanation of symbols]

[0122] 1. Rolling mill 2 Camera 3. Image Processing Device 4 Heater 5 Tilt mechanism 6. Pass / fail judgment device 7. Rolling control device 8 Data Server 9 Machine Learning Devices 10 Control parameter estimation device S steel plate SA steel plate sample

Claims

1. A shape measuring method for measuring a shape of a band-like object, comprising the steps of: When the reference plane of the surface of the belt-like object is a plane α, The angle φ between the orthogonal projection of the optical axis of the camera onto the plane α and the conveying direction p of the belt-like object is not 90 degrees. an imaging step of capturing an image of thermal radiation light from the belt-shaped object; an image processing step of calculating an index of a surface shape of the belt-like object based on the radiance of the belt-like object in the obtained image; A method for measuring the shape of a strip-shaped object, comprising:

2. 2. The method for measuring the shape of a belt-like object according to claim 1, wherein the image processing step extracts linear components parallel to a transport direction of the belt-like object from the radiance of the belt-like object.

3. 2. The method for measuring the shape of a belt-like object according to claim 1, wherein in said imaging step, an angle .theta. between said plane .alpha. and an optical axis of said camera is set to 20 degrees or less.

4. The shape measuring method of a strip-like object as described in claim 1, wherein the image processing step calculates, from the obtained light and dark pattern of the strip-like object, one or more of the steepness, wave height, wave pitch, elongation amount, and elongation rate at each position in the width direction of the surface of the strip-like object as the index.

5. A method for controlling the shape of a strip-like object, comprising: measuring the shape of the strip-like object using a method for measuring the shape of the strip-like object according to any one of claims 1 to 4; and controlling the shape of the strip-like object to a desired shape based on the measurement results.

6. A method for manufacturing a belt-like object, comprising the steps of: measuring a shape of the belt-like object by the method for measuring a shape of the belt-like object according to any one of claims 1 to 4; and manufacturing the belt-like object based on the measurement result.

7. 5. A quality control method for a web-like object, comprising the steps of: measuring a shape of the web-like object by the method for measuring a shape of the web-like object according to claim 1; and controlling the quality of the web-like object based on a measurement result.

8. A shape measuring device for measuring a shape of a belt-like object, comprising: When the reference plane of the surface of the belt-like object is a plane α, The angle φ between the orthogonal projection of the optical axis of the camera onto the plane α and the conveying direction p of the belt-like object is not 90 degrees. an imaging means for capturing an image of thermal radiation light from the belt-shaped object; an image processing means for calculating an index of a surface shape of the belt-like object based on the radiance of the belt-like object in the obtained image; An apparatus for measuring the shape of a strip-shaped object comprising:

9. A manufacturing facility for a web-like object, comprising the device for measuring the shape of a web-like object according to claim 8.

Images