Abrasive plane image acquisition device, acquisition program, and abrasive plane image acquisition method

Abstract

To acquire an appropriate in-focus image as an image indicating an abrasive plane of a rotating grinding wheel in a short time.SOLUTION: A storage part 56 stores an input image 31 which is obtained by photographing an abrasive plane of a grinding wheel as an acquisition object, the input image 31 having the imaged part including information on blurring of the image so as to extend in a rotating direction of the grinding wheel. The storage part 56 stores a machine-learned learning unit 32 using teacher data 33. Example data of the teacher data 33 is constituted of a photographic image obtained by photographing the abrasive plane of the grinding wheel for teacher data creation so that the imaged part includes the information on blurring of the image so as to extend in the rotating direction of the grinding wheel. Correct answer data of the teacher data 33 is constituted of a photographic image obtained by photographing the abrasive plane of the grinding wheel for teacher data creation in an in-focus state. An output part 57 outputs an output image 34 which indicates the abrasive plane corresponding to the input image 31, the output image 34 indicating the abrasive plane in the in-focus state, using the input image 31 as input data, from the learning unit 32.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a grinding surface image acquisition device, an acquisition program, and a grinding surface image acquisition method. [Background technology]

[0002] In grinding processing using a grinding device, the finish quality of the machined surface of a workpiece depends on the condition of the machining surface (so-called grinding surface) of the rotating grinding wheel used as a grinding tool. Patent Document 1 discloses a technique for capturing an image of the grinding surface of a rotating grinding wheel in order to check the condition of the grinding surface. In Patent Document 1, the image of the grinding surface is captured to determine the level of wear and dirt on the grinding surface. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2004-42158 Summary of the Invention [Problem to be solved by the invention]

[0004] Here, it is conceivable to image the grinding surface of the rotary grinding wheel while the rotary grinding wheel is rotating. This makes it possible to shorten the time required to acquire an image of the grinding surface of the rotary grinding wheel. However, in this case, if the rotation speed of the rotary grinding wheel is increased too much, the captured image will be blurred. Thus, when imaging the grinding surface of the rotary grinding wheel, there is a limit to how fast the rotation speed of the rotary grinding wheel can be increased due to the performance of the camera. Therefore, it can be said that there is also a limit to how quickly the time required to acquire an image can be shortened. [Means for solving the problem]

[0005] The grinding surface image acquisition device for solving the above problem is a grinding surface image acquisition device that acquires an image showing the grinding surface of a rotary grinding wheel, and includes: an input unit that stores the input image, which is an input image composed of an image of the grinding surface of the rotary grinding wheel to be acquired and includes information about the image blurring so that the imaged portion extends in the rotation direction of the rotary grinding wheel; a memory unit that stores a trained learning machine that has been machine-learned using teacher data that includes example data composed of an image of the grinding surface of the rotary grinding wheel for creating teacher data that includes information about the image blurring so that the imaged portion extends in the rotation direction; and correct answer data composed of an image of the grinding surface of the rotary grinding wheel for creating the teacher data that is captured in focus; and an output unit that uses the input image as input data and outputs from the trained learning machine an image showing the grinding surface that corresponds to the input image and shows the grinding surface in focus.

[0006] The acquisition program for solving the above problem is an acquisition program that causes an electronic control device provided in the grinding surface image acquisition device to execute the processing of each of the above parts provided in the grinding surface image acquisition device.

[0007] The grinding surface image acquisition method for solving the above problem is a grinding surface image acquisition method for acquiring an image showing the grinding surface of a rotary grinding wheel, and includes an input step of storing the input image, which is an image of the grinding surface of the rotary grinding wheel to be acquired, in an input unit of a grinding surface image acquisition device, and which includes information about the fact that the image blurs so that the imaged portion extends in the rotation direction of the rotary grinding wheel; a storage step of training a learning machine using teacher data including example data composed of imaged images of the grinding surface of the rotary grinding wheel for use in creating teacher data, the example data including information about the fact that the image blurs so that the imaged portion extends in the rotation direction, and ground truth data composed of imaged images of the grinding surface of the rotary grinding wheel for use in creating the teacher data, the image being acquired in focus, and then storing the learning machine in a memory unit of the grinding surface image acquisition device; and an output step of outputting an image showing the grinding surface of the rotary grinding wheel to be acquired in focus from the trained learning machine stored in the memory unit, using the input image as input data.

[0008] In the above-described grinding surface image acquisition device, acquisition program, and grinding surface image acquisition method, when capturing an image of the grinding surface of a rotating grindstone rotating at high speed, there is a risk of the image being blurred so that the captured portion extends in the direction of rotation of the grindstone. According to the above-described grinding surface image acquisition device, acquisition program, and grinding surface image acquisition method, when capturing an image of the grinding surface of the rotating grindstone to capture an image of the grinding surface of the rotating grindstone, image blurring is tolerated. This makes it possible to capture an image of the grinding surface of the rotating grindstone while it is rotating at high speed, thereby enabling the captured image, specifically the input image, to be acquired in a short period of time. Then, based on this input image, a trained learning machine can be used to acquire an image of the grinding surface in a focused state. Therefore, an image in a focused state can be acquired as an image of the grinding surface of the rotating grindstone in a short period of time. [Effects of the Invention]

[0009] According to the present invention, it is possible to obtain an appropriately focused image showing the grinding surface of a grinding wheel in a short period of time. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a schematic diagram showing a schematic configuration of an automatic grinding device to which an abrasive surface image acquisition device according to an embodiment is applied; [Figure 2] FIG. 2 is a block diagram showing a schematic configuration of the grinding surface image acquisition device. [Figure 3] 1 is a schematic diagram showing the structure of a camera unit. [Figure 4] 1 is a schematic diagram showing an input image. [Figure 5] 1 is a schematic diagram illustrating an image captured by a camera. [Figure 6] 1 is a schematic diagram showing training data. [Figure 7] 10 is a flowchart showing the execution procedure of an image acquisition process. [Figure 8] 1 is a schematic diagram showing the relationship between the grinding surface of a grindstone and the imaging range of a camera. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, an embodiment of a grinding surface image acquisition device, an acquisition program, and a grinding surface image acquisition method will be described with reference to FIGS. <Automatic grinding device 20> As shown in FIG. 1, the grinding surface image acquisition device 30 of this embodiment is applied to an automatic grinding machine 20. This automatic grinding machine 20 is a numerically controlled (NC) surface grinding machine that uses a rotary grinding wheel (hereinafter referred to as grinding wheel 21) to grind the surface of a workpiece (not shown). The grinding wheel 21 for grinding has an outer peripheral surface that forms a grinding surface 211. Specifically, the grinding wheel 21 has a structure in which a large number of abrasive grains are fixed to the outer peripheral surface of a cylindrical base material with a binder. The grinding wheel 21 is rotatably supported by a grinding wheel support part 22. The grinding wheel 21 and the grinding wheel support part 22 are movable relative to a base 23 in the vertical direction (hereinafter referred to as the Y direction) and the horizontal direction, specifically the depth direction in FIG. 1 (hereinafter referred to as the Z direction). In the automatic grinding machine 20, the grinding wheel 21 is brought into contact with the workpiece while being rotationally driven, thereby grinding the surface of the workpiece.

[0012] The automatic grinding device 20 has a table 24 as a support base for supporting a workpiece. The table 24 is movable in a horizontal direction perpendicular to both the Z direction and the Y direction, specifically in the left-right direction in FIG. 1 (hereinafter referred to as the X direction). In the automatic grinding device 20, the workpiece on the table 24 can be moved by moving the table 24 in the X direction. This allows the relative positions of the grinding wheel 21 and the workpiece in the X direction to be changed.

[0013] 1 and 2, the automatic grinding device 20 has an operation control unit 25 that controls the operation of the device. The operation control unit 25 has an X-axis drive unit 26, a Y-axis drive unit 27, a Z-axis drive unit 28, and a grindstone drive unit 29.

[0014] The automatic grinding device 20 can change the relative positions of the grinding wheel 21 and the workpiece in the X direction, the Y direction, and the Z direction, respectively, by moving the grinding wheel 21 in the Y direction and the Z direction and by moving the table 24 in the X direction. The X-axis drive unit 26 is a device for moving the table 24 in the X direction relative to the base 23. The X-axis drive unit 26 includes a ball screw mechanism, a servo motor, and the like (not shown). The X-direction position of the table 24 relative to the base 23 is controlled by controlling the operation of the X-axis drive unit 26. The Y-axis drive unit 27 is a device for moving the grinding wheel 21 and the grinding wheel support unit 22 in the Y direction relative to the base 23. The Y-axis drive unit 27 includes a ball screw mechanism, a servo motor, and the like (not shown). The Y-direction position of the grinding wheel 21 relative to the base 23 is controlled by controlling the operation of the Y-axis drive unit 27. The Z-axis drive unit 28 is a device for moving the grinding wheel 21 and the grinding wheel support unit 22 in the Z direction relative to the base 23. The Y-axis driving unit 27 has a ball screw mechanism, a servo motor, etc. (not shown). Through the operation control of the Y-axis driving unit 27, the position of the grinding wheel 21 in the Z direction relative to the base 23 is controlled.

[0015] The grinding wheel driving unit 29 includes an electric motor connected to the rotation shaft of the grinding wheel 21, a rotation phase sensor that detects the rotation phase of the grinding wheel 21, and the like. In the operation control of the grinding wheel driving unit 29 (more specifically, the electric motor), the grinding wheel 21 is basically rotated at a constant speed. The rotation speed of the grinding wheel 21 is set based on the processing conditions input to the automatic grinding device 20 and is a speed that matches the processing conditions.

[0016] <Grinding surface image acquisition device 30> The grinding surface image acquisition device 30 of this embodiment will be described in detail below. The grinding surface image acquisition device 30 is a device for acquiring an image showing the grinding surface 211 of the grinding wheel 21. In this embodiment, it is possible to check, for example, the condition of the grinding surface 211 of the grinding wheel 21 based on the acquired image showing the grinding surface 211 of the grinding wheel 21. The grinding surface image acquisition device 30 includes a camera unit 40 and an electronic control device 50.

[0017] <Camera Unit 40> 1 to 3, the camera unit 40 captures an image of the grinding surface 211 of the grindstone 21. The camera unit 40 includes a camera 41 as an imaging unit, and an illumination unit 43.

[0018] <Camera 41> As shown in FIGS. 1 and 3, the camera 41 is disposed below the grinding wheel 21. The camera 41 captures an image of the grinding surface 211 of the grinding wheel 21 from a direction perpendicular to the grinding surface 211 (more specifically, the tangent plane of the grinding surface 211 indicated by the dashed line in FIG. 3). In this embodiment, the camera 41 captures an image of the grinding surface 211 while the grinding wheel 21 is rotating at a predetermined speed VW. The captured image captured by the camera 41 is stored as an input image 31 in the electronic control device 50, which will be described later. In this embodiment, the grinding wheel 21 attached to the automatic grinding machine 20 when the camera 41 captures an image corresponds to the rotating grinding wheel to be acquired.

[0019] <Lighting Department 43> As shown in FIG. 3, the illumination unit 43 illuminates the lower end portion of the grinding surface 211, i.e., the area to be imaged by the camera 41 (hereinafter, referred to as the image-capturing area RE). The illumination unit 43 includes a first illumination unit 45 and a second illumination unit 46. The first illumination unit 45 irradiates the image-capturing area RE of the grinding surface 211 with first illumination light 45L having a first emission color (e.g., blue) from a direction perpendicular to the grinding surface 211 (more specifically, the tangent plane of the grinding surface 211 shown by the dashed-dotted line in FIG. 3). The second illumination unit 46 irradiates the image-capturing area RE of the grinding surface 211 with second illumination light 46L having a second emission color (e.g., white) different from the first emission color from a direction oblique to the grinding surface 211 (more specifically, the tangent plane of the grinding surface 211 shown by the dashed-dotted line in FIG. 3).

[0020] In this embodiment, the camera unit 40 is detachable from the automatic grinding apparatus 20. The camera unit 40 is attached to the automatic grinding apparatus 20 when imaging the grinding surface 211. In the camera unit 40, when imaging the grinding surface 211 using the camera 41, the illumination unit 43 illuminates the imaging target area RE of the grinding surface 211. Note that in this embodiment, when grinding is performed by the automatic grinding apparatus 20, the camera unit 40 is detached from the automatic grinding apparatus 20.

[0021] <Electronic control device 50> The electronic control device 50 executes various controls for acquiring an image showing the grinding surface 211 of the grinding wheel 21 .

[0022] The electronic control device 50 includes a PU 51, a ROM 52, a RAM 53, an operation input unit 54, a display unit 55, and a memory unit 56. The PU 51 is a processing unit such as a CPU, a GPU, and a TPU. The operation input unit 54 is an input device such as a mouse, a keyboard, a touch panel, and buttons. The operation input unit 54 is operated when configuring various settings for the grinding surface image acquisition device 30 or when operating the grinding surface image acquisition device 30. The display unit 55 includes a display device such as an LCD display or an OLED display. The display unit 55 displays various information related to the acquisition of images, such as images of the grinding surface 211 acquired through the image acquisition process described below. The memory unit 56 is composed of non-volatile memory such as a hard disk drive or solid-state drive that can be written to and read from as needed. The memory unit 56 includes a memory area for storing various execution programs 35, a memory area for storing training data 33 used in machine learning by the learner 32, and a memory area for storing the learned learner 32. The storage unit 56 also has a storage area as an input unit that stores an image (the input image 31) of the grinding surface 211 of the grinding wheel 21 to be acquired. The execution program 35 includes a program for causing the learning device 32 to execute machine learning, and an acquisition program for causing the learning device 32 to execute various processes related to acquiring an image showing the grinding surface 211 of the grinding wheel 21.

[0023] The electronic control device 50 includes an output unit 57 as a functional unit. The output unit 57 uses the input image 31 as input data and outputs, from the trained learning device 32 stored in the memory unit 56, an image showing the grinding surface 211 corresponding to the input image 31 (hereinafter, output image 34), which shows the grinding surface 211 in focus.

[0024] <Image capture processing> In this embodiment, in order to acquire the input image 31, an imaging process is executed in which the camera 41 captures an image of the grinding surface 211 of the grindstone 21.

[0025] In the imaging process, first, the grinding wheel 21 to be acquired is attached to the automatic grinding device 20, and the grinding wheel 21 is driven to rotate. Then, in this state, an image of the grinding surface 211 is captured by the camera 41. In this embodiment, patterns for the rotational drive pattern of the grinding wheel 21, the position control pattern of the camera 41, and the imaging pattern of the camera 41 that enable the camera 41 to efficiently capture the entire surface of the grinding surface 211 are determined in advance and stored in the electronic control device 50.

[0026] Possible methods for storing the above patterns in the memory unit 56 include the following (Method A) and (Method B). (Method A) After the user of the automatic grinding device 20 installs the grinding wheel 21 that will actually be used, the user operates the automatic grinding device 20 to determine the above patterns suitable for the grinding wheel 21, and stores these patterns in the electronic control device 50. (Method B) Based on the results of various experiments and simulations, the manufacturer of the automatic grinding device 20 determines in advance the above patterns that will enable efficient imaging of the entire grinding surface 211 of the grinding wheel 21. Data related to these patterns is then stored in the automatic grinding device 20 before shipment, or in an automatic grinding device 20 installed in the user's factory.

[0027] When capturing an image of the grinding surface 211 of the grinding wheel 21, the operation of the grinding wheel driver 29 is controlled based on the rotational drive pattern of the grinding wheel 21, and the operation of the X-axis driver 26, the Y-axis driver 27, and the Z-axis driver 28 is controlled based on the position control pattern of the camera 41. Furthermore, the camera 41 captures an image of the grinding surface 211 based on the image capturing pattern of the camera 41. The electronic control device 50 then captures image data of the grinding surface 211 captured by the camera 41 and stores the image data in the memory 56. Specifically, the camera 41 captures images of the grinding surface 211 multiple times. The captured images are then combined in a predetermined order, vertically and horizontally, to form a single image (input image 31) showing the entire grinding surface 211, as shown in FIG. 4 . The electronic control device 50 stores the input image 31 thus generated in the memory 56.

[0028] In the grinding surface image acquisition device 30 of this embodiment, the camera 41 captures an image of the grinding surface 211 of the grinding wheel 21 while the grinding wheel 21 is rotating at a predetermined speed VW. Therefore, as shown schematically in FIG. 5 , the image IM captured by the camera 41 may be blurred as if it were elongated in the rotational direction of the grinding wheel 21 due to the grinding surface 211 moving in the rotational direction of the grinding wheel 21 (the up-and-down direction in FIG. 5 ). The solid line in FIG. 5 indicates the abrasive grains when the image is blurred as if it were elongated in the rotational direction, while the dashed line in FIG. 5 indicates the abrasive grains when the image is not blurred. Furthermore, the image IM captured by the camera 41 may be dark overall due to the fast shutter speed used to capture the moving grinding surface 211. In this embodiment, the image IM captured by the camera 41 includes information about the image blurring as if the captured portion is elongated in the rotational direction of the grinding wheel 21 and information about the darkening of the captured image.

[0029] The grinding surface image acquisition device 30 of this embodiment uses the input image 31, which is an image captured by the camera 41, and a trained learning device 32 to generate and output an image showing the grinding surface 211 in a focused, bright state.

[0030] <Learning Module 32> The learning device 32 will be described in detail below. A Generative Adversarial Network (GAN), more specifically an image generation model called "pix2pix," is used as the learner 32. The learner 32 performs machine learning using training data 33. The training data 33 is data for performing machine learning on the learner 32 so that the learner 32 acquires the ability to generate a bright, in-focus image from an image captured by the camera unit 40, i.e., a dark, blurred image.

[0031] <Teacher Data 33> As shown in FIG. 6, the training data 33 is composed of an image data set in which example data 331 and correct answer data 332 are paired.

[0032] <Example data 331> The example data 331 is an image composed of an image of the grinding surface 211 of the grinding wheel 21, which includes information regarding the image being blurred as the captured portion extends in the rotation direction of the grinding wheel 21, and information regarding the captured image being dark.

[0033] The example data 331 can be generated, for example, by the following procedure. First, the grinding wheel 21 for creating the training data is attached to the automatic grinding device 20 (FIG. 1). Then, the imaging process is executed in this state. The captured image acquired through this imaging process is used as the example data 331. Alternatively, it is also possible to use a separate device different from the automatic grinding device 20 to capture an image of the grinding surface 211 of the grinding wheel 21 while rotating the grinding wheel 21 at a predetermined speed VW, and use this captured image as the example data 331. As the example data 331, a single image showing the entire grinding surface 211 is generated.

[0034] <Correct answer data 332> The correct answer data 332 is an image configured from a captured image of the grinding surface 211 of the grinding wheel 21 that is captured in focus and brightly.

[0035] The correct answer data 332 can be generated, for example, by the following procedure. First, the grinding wheel 21 for creating the training data is attached to the automatic grinding device 20. Then, with the grinding wheel 21 stopped or rotating at a relatively slow speed (slower than the predetermined speed VW), the camera 41 captures an image of the grinding surface 211. Specifically, the operation of the grinding wheel driver 29 is controlled based on a predetermined rotational drive pattern of the grinding wheel 21, and the operation of the X-axis driver 26, the Y-axis driver 27, and the Z-axis driver 28 is controlled based on a predetermined position control pattern of the camera 41. Furthermore, the camera 41 captures an image of the grinding surface 211 based on a predetermined imaging pattern of the camera 41. Then, the electronic control device 50 captures image data of the grinding surface 211 captured by the camera 41 and stores the image data in the memory 56. Specifically, the camera 41 captures an image of the grinding surface 211 multiple times. Then, by combining the captured images in a state where they are arranged lengthwise and widthwise in a predetermined order, a single image (correct data 332) showing the entire grinding surface 211 is formed.

[0036] Alternatively, a separate device different from the automatic grinding device 20 may be used to capture images of the grinding surface 211 with the camera 41 while the grinding wheel 21 is stopped from rotating or while the grinding wheel 21 is rotating at a relatively slow speed. In this case, the camera 41 captures images of the grinding surface 211 multiple times, and the captured images are combined in a state where they are arranged vertically and horizontally in a predetermined order, thereby forming a single image (correct answer data 332) showing the entire grinding surface 211.

[0037] As shown in FIG. 6 , in this embodiment, a large number of image data sets are created, each pair consisting of example data 331 and correct answer data 332. Then, as shown in FIG. 2 , these image data sets are used as training data 33 for the learner 32. More specifically, the electronic control device 50 extracts one of the multiple image data sets that make up the training data 33 and uses this as input data to cause the learner 32 to perform machine learning. This learning process is repeatedly performed for each image data set that makes up the training data 33. Then, the machine learning model constructed through the execution of machine learning is stored in the storage unit 56 as the trained learner 32. Note that in this embodiment, the process of storing the trained learner 32 in the storage unit 56 corresponds to the storage process.

[0038] When the trained learning device 32 receives the input image 31, which is an image of the grinding surface 211 of the grinding wheel 21 to be acquired, it generates and outputs an image that shows the grinding surface 211 corresponding to the input image 31 and is bright and in focus.

[0039] <Image acquisition process> The process of acquiring an image showing the grinding surface 211 (image acquisition process) will be described in detail below. Fig. 7 shows the execution procedure of the image acquisition process. A series of processes shown in the flowchart of Fig. 7 is executed by the electronic control unit 50 as processes at predetermined intervals.

[0040] 7, in this process, first, an image (input image 31) of the grinding surface 211 of the grinding wheel 21 attached to the automatic grinding device 20 is stored in the storage unit 56 (step S11). Specifically, the imaging process is executed. Then, the input image 31 is formed based on the image data acquired by the imaging process, and the input image 31 is stored in the storage unit 56. In this embodiment, the process of step S11 corresponds to an input step.

[0041] Thereafter, using the input image 31 stored in the memory unit 56 as input data, an image showing the grinding surface 211 corresponding to the input image 31 (hereinafter referred to as output image 34) is generated and output from the trained learning device 32 stored in the memory unit 56 (step S12). In this embodiment, a bright image in focus is output as the output image 34. In this embodiment, the processing of step S12 corresponds to the output step.

[0042] <Actions and Effects of This Embodiment> The operation and effects of this embodiment will be described. (1) The grinding surface image acquisition device 30 includes an input unit, a memory unit 56, and an output unit 57. The input unit stores an input image 31 composed of a captured image of the grinding surface 211 of the grinding wheel 21 to be acquired, the input image 31 including information about image blurring such that the captured portion extends in the rotation direction of the grinding wheel 21. The memory unit 56 stores a trained learner 32 that has been machine-learned using teacher data 33 including example data 331 and ground truth data 332. The example data 331 is composed of captured images of the grinding surface 211 of the grinding wheel 21 used to create the teacher data, including information about image blurring such that the captured portion extends in the rotation direction of the grinding wheel 21. The ground truth data 332 is composed of captured images of the grinding surface 211 of the grinding wheel 21 used to create the teacher data, captured in focus. The output unit 57 uses the input image 31 as input data and outputs, from the trained learning device 32 stored in the memory unit 56, an output image 34 showing the grinding surface 211 corresponding to the input image 31, which is also an output image 34 showing the grinding surface 211 in focus.

[0043] According to the above configuration, by using the trained learning device 32, it is possible to obtain a focused image of the grinding surface 211 based on the captured image captured by the camera unit 40, i.e., the blurred input image 31. Therefore, when capturing an image of the grinding surface 211 of the grinding wheel 21 to obtain the output image 34, image blurring is tolerated. This makes it possible to capture an image of the grinding surface 211 of the grinding wheel 21 while the grinding wheel 21 is rotating at high speed, so that the captured image, specifically the input image 31, can be obtained in a short time. Then, based on this input image 31, it is possible to obtain the output image 34, which is an image of the grinding surface 211 in a focused state, using the trained learning device 32. Therefore, according to the above configuration, it is possible to obtain the focused output image 34 as an image of the grinding surface 211 of the grinding wheel 21 in a short time.

[0044] Furthermore, since image blurring in the input image 31 is permitted, the image of the grinding surface 211 is captured while the grinding wheel 21 is rotating at high speed, but an output image 34 showing the grinding surface 211 of the grinding wheel 21 can be obtained using an inexpensive camera 41 with relatively low performance.

[0045] (2) The example data 331 is composed of captured images of the grinding surface 211 of the grinding wheel 21 used to create the training data, which include information about the darkening of the image. The correct answer data 332 is composed of captured images of the grinding surface 211 of the grinding wheel 21 used to create the training data, which are captured in a state where the image is bright.

[0046] According to the above configuration, by using the trained learning device 32, it is possible to acquire an image of the grinding surface 211 in a bright state based on the captured image captured by the camera unit 40, i.e., the darkened input image 31. Therefore, when capturing an image of the grinding surface 211 of the grinding wheel 21 to acquire the output image 34, it is acceptable for the captured image to be dark. This makes it possible to capture an image of the grinding surface 211 of the grinding wheel 21 while the grinding wheel 21 is rotating at high speed, so that the captured image, specifically the input image 31, can be acquired in a short time. Then, based on this input image 31, it is possible to acquire the output image 34, which is an image of the grinding surface 211 in a moderately bright state, using the trained learning device 32. Therefore, according to the above configuration, it is possible to acquire the output image 34 in a moderately bright state as an image of the grinding surface 211 of the grinding wheel 21 in a short time.

[0047] Furthermore, since the input image 31 is allowed to be dark, the image of the grinding surface 211 is captured while the grinding wheel 21 is rotating at high speed, but an output image 34 showing the grinding surface 211 of the grinding wheel 21 can be obtained using an inexpensive camera 41 with relatively low performance.

[0048] (3) The grinding wheel 21 has an outer peripheral surface that forms a grinding surface 211 . 8, in this embodiment, the grinding surface 211 of the grinding wheel 21 is curved in one direction, so if the imaging range P1 in one imaging is made too wide, both end portions P2 of the imaging range P1 in the curvature direction will be outside the range AR in focus. For this reason, it can be said that the imaging range P1 in one imaging of the grinding wheel 21 is likely to be narrow, and it can also be said that it is likely to take a long time to image the grinding surface 211.

[0049] According to this embodiment, even if the input image 31 captured by the camera 41 is an out-of-focus image, by using a trained learning device 32, it is possible to obtain an output image 34 showing the grinding surface 211 in a focused state based on the input image 31. Therefore, when capturing an image of the grinding surface 211 of the grinding wheel 21 to obtain the input image 31, it is acceptable for both end portions P2 in the curvature direction of the imaging range P1 to be out of focus. This makes it possible to widen the imaging range P1 in one imaging session, thereby shortening the time required to obtain the input image 31. Therefore, according to this embodiment, an in-focus image can be obtained in a short time as the output image 34 showing the grinding surface 211 of the grinding wheel 21.

[0050] (4) Each of the input image 31, the example data 331, and the correct answer data 332 is a single image showing the entire grinding surface 211. According to the above configuration, with a simple configuration in which a single input image 31 capturing the entire grinding surface 211 is used as input data, an output image 34 showing the entire grinding surface 211 can be obtained.

[0051] <Example of change> The above embodiment can be modified as follows: The above embodiment and the following modifications can be combined with each other within the scope of technical compatibility.

[0052] The grinding wheel 21 used to form the correct answer data 332 may be a grinding wheel 21 with debris such as chips and grinding fluid still attached to the grinding surface 211, or a grinding wheel 21 with the debris removed from the grinding surface 211. When a grinding wheel 21 with debris still attached is used, an output image 34 showing the grinding surface 211 with the debris attached can be obtained as an output image 34 from the trained learning device 32. The state of the grinding surface 211 can be confirmed based on this output image 34. On the other hand, when a grinding wheel 21 with debris removed from the grinding surface 211 is used, an output image 34 showing the grinding surface 211 with no debris attached can be obtained as an output image 34 from the trained learning device 32. The state of the grinding surface 211 can be confirmed based on this output image 34.

[0053] The camera unit 40 may be configured as one unit with the automatic grinding device 20. In this configuration, it becomes possible to acquire an output image 34 showing the grinding surface 211 of the grinding wheel 21 while the grinding wheel 21 is rotating between grinding processes of the workpiece by the automatic grinding device 20. Then, based on this output image 34, the state of the grinding surface 211 of the grinding wheel 21 can be confirmed. With this configuration, the automatic grinding device 20 can be operated efficiently while the state of the grinding wheel 21 is being confirmed at appropriate times.

[0054] The camera unit 40 may be disposed to the side of the grindstone 21 or above the grindstone 21. The structure of the illumination unit 43 can be changed as desired. For example, one of the first illumination unit 45 and the second illumination unit 46 may be omitted. The first emission color of the first illumination light 45L from the first illumination unit 45 and the second emission color of the second illumination light 46L from the second illumination unit 46 can be changed as desired.

[0055] A separate device other than the automatic grinding device 20 and its camera may be used to capture an image of the grinding surface 211 of the grinding wheel 21 as the target grinding wheel 21 is rotated at a predetermined speed VW, and the input image 31 may be formed based on the captured image. In this case, the input image 31 formed as described above may be stored in the memory unit 56 of the electronic control device 50 in step S11 of the image acquisition process (FIG. 7). When this configuration is adopted, the camera unit 40 may be omitted.

[0056] The work of storing the learned learning device 32 in the electronic control device 50 can be performed in any manner, such as the following (Work A) to (Work C). (Task A) Using the automatic grinding device 20 and grinding surface image acquisition device 30 used by the user, teacher data 33 is acquired, and the learning device 32 is trained by machine learning using the teacher data 33.

[0057] (Work B) The manufacturer of the automatic grinding device 20 or the manufacturer of the grinding wheel 21 provides the training data 33 corresponding to the grinding wheel 21 that is actually used. The training data 33 is then stored in the electronic control device 50 of the grinding surface image acquisition device 30 used by the user, thereby allowing the learning device 32 to perform machine learning.

[0058] (Operation C) When manufacturing the grinding surface image acquisition device 30, the learned learning device 32 is stored in the electronic control device 50. The grinding wheel 21 can be a general grinding wheel containing general abrasive grains or a superabrasive grinding wheel containing superabrasive grains. Because superabrasive grains are smaller than general abrasive grains, capturing a high-magnification image of the grinding surface of a superabrasive grinding wheel is essential to accurately assess the condition of the grinding surface. Therefore, when capturing an image of a superabrasive grinding wheel, the capture range per capture tends to be narrower than when capturing an image of a general grinding wheel, and the time required to capture an image of the grinding surface tends to be longer. According to the above embodiment, even when such a superabrasive grinding wheel is used as the grinding wheel 21, a bright, in-focus output image 34 can be captured in a short time as an image of the grinding surface 211 of the grinding wheel 21.

[0059] The input image 31 is not limited to a single image showing the entire grinding surface 211, but may also be a single image showing a portion (e.g., half) of the grinding surface 211, or multiple images obtained by dividing an image showing the entire grinding surface 211 into multiple parts. When multiple images are used as the input image 31, the image acquisition process (see FIG. 7) may be performed for each of the multiple images.

[0060] The input image 31 captured by the camera unit 40 can be used as input data either at the size at which it was captured or after enlarging or reducing it. This configuration allows for a high degree of freedom in the imaging process for acquiring the input image 31. For example, the following configurations (Configuration A) and (Configuration B) are conceivable.

[0061] (Configuration A) The example data 331 and the correct answer data 332 are constructed from captured images of the grinding surface 211 taken at a high magnification (M1). The input image 31 is constructed from captured images of the grinding surface 211 taken at a relatively low magnification (M2). The input image 31 is enlarged by a predetermined ratio R1 (R1=M1 / M2) and used as input data.

[0062] Here, when the abrasive grains of the grinding wheel 21 are small, it is preferable to image the grinding surface 211 at a high magnification in order to capture the characteristics of the grinding surface 211. However, when the grinding surface 211 is imaged at a high magnification, the imaging range in one image capture becomes narrower, which creates a trade-off in that it takes a long time to image the entire grinding surface 211.

[0063] According to the above configuration A, an input image 31, which is an image of the grinding surface 211 captured at a relatively low magnification M2, is used as input data, and an output image 34 equivalent to an image of the grinding surface 211 captured at a high magnification M1 is generated and output from the trained learning device 32. Therefore, when the abrasive grains of the grinding wheel 21 are small, an image equivalent to an image of the grinding surface 211 captured at a high magnification can be obtained as the output image 34 showing the grinding surface 211 of the grinding wheel 21, without capturing an image of the grinding surface 211 at a high magnification to obtain the input image 31.

[0064] (Configuration B) The example data 331 and the correct answer data 332 are constructed from images of the grinding surface 211 captured at a low magnification (M3). The input image 31 is constructed from images of the grinding surface 211 captured at a relatively high magnification (M4). The input image 31 is reduced by a predetermined ratio R2 (R2 = M4 / M3) and used as input data.

[0065] According to the above-described configuration B, an input image 31, which is an image of the grinding surface 211 captured at a relatively high magnification M4, is used as input data, and an output image 34 corresponding to an image of the grinding surface 211 captured at a low magnification M3 is generated and output from the trained learning device 32. Therefore, when the abrasive grains of the grinding wheel 21 are large, an image corresponding to an image of the grinding surface 211 captured at a low magnification can be acquired as the output image 34 showing the grinding surface 211 of the grinding wheel 21, without capturing an image of the grinding surface 211 at a low magnification to acquire the input image 31.

[0066] As the learner 32, any image generation model other than "pix2pix" can be used as long as it can generate a bright, in-focus image from a dark, blurred image. It is also possible to use an image generation model other than a generative adversarial network as the learner 32.

[0067] The input image 31 may be composed of a captured image of the grinding surface 211 of the grinding wheel 21 to be acquired so as not to include information related to the darkening of the image. In this case, the example data 331 may be composed of a captured image of the grinding surface 211 of the grinding wheel 21 used to create training data so as not to include information related to the darkening of the image. Specifically, the input image 31 and the example data 331 may be composed of captured images of the grinding surface 211 captured in an imaging environment in which the captured image is not dark overall. With the above configuration, the output image 34 showing the grinding surface 211 in focus can be obtained in a short time based on the input image 31 using a trained learning device 32.

[0068] The grinding surface image acquisition device, acquisition program, and grinding surface image acquisition method according to the above-described embodiments can be applied to a rotating grinding wheel for circumferential grinding, in which the outer peripheral surface of a cylindrical substrate serves as the grinding surface, as well as to a rotating grinding wheel for front grinding, in which the bottom surface of a cylindrical substrate serves as the grinding surface.

[0069] <Additional Notes> The above embodiment includes the configurations described in the following supplementary notes. [Appendix 1] A grinding surface image acquisition device for acquiring an image showing the grinding surface of a rotary grinding wheel, the grinding surface image acquisition device comprising: an input unit that stores the input image, which is an input image composed of an image of the grinding surface of the rotary grinding wheel to be acquired, and which includes information about the image blurring so that the imaged portion extends in the rotational direction of the rotary grinding wheel; a memory unit that stores a trained learning device that has been machine-learned using teacher data including example data composed of an image of the grinding surface of the rotary grinding wheel for creating teacher data, which includes information about the image blurring so that the imaged portion extends in the rotational direction, and correct answer data composed of an image of the grinding surface of the rotary grinding wheel for creating the teacher data, which is captured in focus; and an output unit that uses the input image as input data and outputs from the trained learning device an image showing the grinding surface that corresponds to the input image and shows the grinding surface in focus.

[0070] [Appendix 2] The grinding surface image acquisition device described in [Appendix 1], wherein the input image is composed of an image of the grinding surface of the grinding wheel to be acquired so as to include information regarding the image becoming darker, the example data is composed of an image of the grinding surface of the grinding wheel for use in creating the training data so as to include information regarding the image becoming darker, and the correct answer data is composed of an image of the grinding surface of the grinding wheel for use in creating the training data so as to include information regarding the image becoming brighter.

[0071] [Appendix 3] The grinding surface image acquisition device according to [Appendix 1] or [Appendix 2], wherein the rotating grindstone has an outer peripheral surface that becomes the grinding surface. [Appendix 4] A grinding surface image acquisition device described in any one of [Appendix 1] to [Appendix 3], wherein each of the input image, the example data, and the correct answer data is a single image showing the entire grinding surface.

[0072] [Appendix 5] [Appendix 1] to [Appendix 4]. An acquisition program that causes an electronic control device provided in the grinding surface image acquisition device to execute the processing of each of the units provided in the grinding surface image acquisition device.

[0073] [Appendix 6] A grinding surface image acquisition method for acquiring an image showing the grinding surface of a rotary grinding wheel, the method comprising: an input step of storing, in an input unit of a grinding surface image acquisition device, an input image which is an image of the grinding surface of the rotary grinding wheel to be acquired and which includes information about the image blurring so that the imaged portion extends in the rotational direction of the rotary grinding wheel; a storage step of training a learning machine using teacher data including example data made up of imaged images of the grinding surface of the rotary grinding wheel for use in creating teacher data so as to include information about the image blurring so that the imaged portion extends in the rotational direction, and ground truth data made up of imaged images of the grinding surface of the rotary grinding wheel for use in creating the teacher data, the example data being made up of imaged images of the grinding surface of the rotary grinding wheel in a focused state; and an output step of outputting, as input data, an image showing the grinding surface of the rotary grinding wheel to be acquired in a focused state from the trained learning machine stored in the storage unit. [Explanation of symbols]

[0074] RE: Image target area IM…Image P1...Image capture range P2: Both ends AR…Range 20...Automatic grinding device 21...Grinding stone 211...Abrasive surface 22...Grinding stone support part 23...Foundation 24...Table 25...Operation control unit 26...X-axis drive unit 27...Y-axis drive unit 28...Z-axis drive unit 29...Grinding wheel drive unit 30... Grinding surface image acquisition device 31...Input image 32...Learning unit 33…Teacher data 331...Example data 332...Correct data 34...Output image 35...Execution program 40...Camera unit 41...Camera 43...Lighting section 45...First irradiation section 45L...First lighting 46…Second irradiation section 46L…Second illumination light 50...Electronic control device 51...CPU 52...ROM 53...RAM 54...Operation input section 55...Display section 56...Storage section 57...Output section

Claims

1. A grinding surface image acquisition device for acquiring an image showing a grinding surface of a grinding wheel, an input unit that stores an input image that is an image of the grinding surface of the grinding wheel to be acquired, the input image including information about the image blurring such that the captured portion extends in the rotation direction of the grinding wheel; a storage unit that stores a trained learning machine that has been machine-learned using training data including example data that is composed of captured images of the grinding surface of the rotary grindstone for use in creating training data, the example data being composed of captured images of the grinding surface of the rotary grindstone for use in creating training data, the captured images being captured in focus, the example data being composed of captured images of the grinding surface of the rotary grindstone for use in creating training data, the captured images being captured in focus, and a storage unit that stores a trained learning machine that has been machine-learned using training data including example data that is composed of captured images of the grinding surface of the rotary grindstone for use in creating training data, the example data being ... an output unit that uses the input image as input data and outputs, from the trained learning device, an image showing the grinding surface corresponding to the input image and showing the grinding surface in a focused state; A grinding surface image acquisition device comprising:

2. the input image is configured from a captured image of the grinding surface of the grinding wheel of the acquisition target so as to include information regarding the darkening of the image; the example data is composed of a captured image of the grinding surface of the grinding wheel for creating the training data, the captured image including information about the darkening of the image; The correct answer data is composed of a captured image of the grinding surface of the grinding wheel used to create the training data, in a bright image state. The grinding surface image acquisition device according to claim 1 .

3. The rotating grindstone has an outer circumferential surface that serves as a grinding surface.

3. The grinding surface image acquisition device according to claim 1 or 2.

4. Each of the input image, the example data, and the correct answer data is a single image showing the entire grinding surface.

3. The grinding surface image acquisition device according to claim 1 or 2.

5. 3. An acquisition program that causes an electronic control device provided in the grinding surface image acquisition device to execute processing of each of the units provided in the grinding surface image acquisition device according to claim 1 or 2.

6. A grinding surface image acquisition method for acquiring an image showing a grinding surface of a grinding wheel, comprising: an input step of storing, in an input unit of the grinding surface image acquisition device, an input image that is an image of the grinding surface of the grinding wheel to be acquired, and that includes information about the image blurring such that the captured portion extends in the rotation direction of the grinding wheel; a storage process in which a learning machine uses training data including example data made up of captured images of the grinding surface of the rotary grindstone for use in creating training data, the example data including information about the blurring of the image so that the captured image portion extends in the rotation direction, and correct answer data made up of captured images of the grinding surface of the rotary grindstone for use in creating training data, the correct answer data being captured in focus, and then the learning machine is stored in a storage unit of the grinding surface image acquisition device; an output step of outputting an image showing a focused grinding surface of the grinding wheel of the acquisition target from the learned learning device stored in the storage unit using the input image as input data; A grinding surface image acquisition method comprising:

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