Processing support device and processing system

Abstract

To provide a processing support device and a processing device which can properly detect a spot that requires re-processing.SOLUTION: A processing support device E comprises: a presentation unit 15A which presents information on a plurality of types of workpiece surfaces; a designation unit 15B which allows any of the information on the plurality of types of workpiece surfaces presented by the presentation unit 15A to be designated from the outside; an imaging unit 12 which acquires a photographed image of a processing object workpiece K after processing of the processing object workpiece K; and a re-processing determination unit 24 which determines a spot that requires re-processing of the processing object workpiece K on the basis of the information designated by the designation unit 15B and the information obtained from the photographed image.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a machining support device and a machining system. [Background technology]

[0002] Patent Document 1 discloses an apparatus for detecting surface defects on a workpiece after polishing in a processing apparatus that performs polishing, and for performing re-polishing so that the detected surface defects are removed. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2016-78150 A Summary of the Invention [Problem to be solved by the invention]

[0004] The workpiece surface may contain various surface patterns, from surface patterns that should be removed by machining to surface patterns that remain after machining. In such cases, it is not possible to easily detect the areas to be remachined as in Patent Document 1.

[0005] An object of the present invention is to provide a processing support device and a processing device that can appropriately detect a portion requiring reprocessing. [Means for solving the problem]

[0006] The processing support device according to the present invention comprises: A presentation unit that presents information on a plurality of types of work surfaces; A designation unit capable of externally designating one of the multiple types of work surface information presented by the presentation unit; An imaging unit for acquiring an image of a workpiece to be processed after the workpiece is processed; a re-machining determination unit that determines a portion of the workpiece that needs to be re-machined based on information designated by the designation unit and information obtained from the captured image; Equipped with 、 The information designated by the designation unit is designated as information indicating a surface condition requiring reprocessing. do. (1) The processing support device according to one aspect of the present invention comprises: Furthermore, the information of the workpiece surface presented by the presentation unit is information indicating the spatial frequency components of the workpiece surface. (2) In addition, a processing support device according to another aspect of the present invention is Furthermore, the information obtained from the captured image is information indicating the spatial frequency components of the workpiece surface in the captured image. (3) In addition, a processing support device according to another aspect of the present invention is Furthermore, the photographing unit acquires photographed images of a plurality of locations of the workpiece to be processed, The AnoGAN processing unit further includes a first image group and a second image group having more areas detected as abnormal than the first image group by AnoGAN, The re-processing determination unit does not determine the locations of the captured images of the first image group that require re-processing, but determines the locations of the captured images of the second image group that require re-processing.

[0007] The present invention Another The processing system of the embodiment includes: An imaging unit for acquiring an image of a workpiece to be processed after the workpiece is processed; a re-machining determination unit that determines a portion of the workpiece that requires re-machining based on information indicating a surface state that requires re-machining and information obtained from the captured image; Equipped with. (1) According to another aspect of the present invention, there is provided a processing support device, Furthermore, the information obtained from the captured image is information indicating the spatial frequency components of the workpiece surface in the captured image. (2) In addition, a processing support device according to another aspect of the present invention is Furthermore, the photographing unit acquires photographed images of a plurality of locations of the workpiece to be processed, The AnoGAN processing unit further includes a first image group and a second image group having more areas detected as abnormal than the first image group by AnoGAN, The re-processing determination unit does not determine the locations of the captured images of the first image group that require re-processing, but determines the locations of the captured images of the second image group that require re-processing.

[0008] The processing system according to the present invention comprises: A processing device that performs processing; The above processing support device, Equipped with. Effect of the Invention

[0009] According to the present invention, it is possible to provide a processing support device and a processing device that can appropriately detect a portion requiring reprocessing. [Brief description of the drawings]

[0010] [Figure 1] 1 is a block diagram showing a processing system according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a diagram for explaining an example of image conversion processing executed by an image processing unit, showing an image before conversion (A) and an image after conversion (B). [Diagram 3] 3A to 3C are diagrams showing examples of a workpiece surface image, an FFT processed image, and an IFFT image processed by an image processing unit. [Figure 4] FIG. 1A is a diagram illustrating a learning process and a judgment process executed by an AnoGAN processing unit. [Diagram 5] 13 is a flowchart showing a surface condition designation process executed by the support processing unit. [Figure 6] FIG. 13 is a display image diagram showing an example of a designation screen for designating a surface condition requiring reprocessing. [Figure 7] 11 is a flowchart showing an automatic machining process executed by a machining control unit and a re-machining determination process. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. FIG. 1 is a block diagram showing a machining system according to an embodiment of the present invention. The machining system 1 according to this embodiment is a system that can determine a portion requiring remachining after machining a workpiece K to be machined, and can remachine the portion. Such processing is performed automatically or semi-automatically. Semi-automatic means that some operations required for processing (for example, operations to start each stage: an operation to start machining, an operation to start determining a portion requiring remachining, an operation to start remachining, etc.) are performed by a user, and the rest are performed automatically.

[0012] Furthermore, the machining system 1 according to this embodiment has a function of presenting information on multiple types of surfaces of the workpiece Ka to the user in advance, and allowing the user to specify the surface that requires re-machining from the presented information on the multiple types of surfaces. The surface information specified by the user determines the location that requires re-machining in the machining process of the above-mentioned machining target workpiece K. Hereinafter, the process of having the user specify the surface information that requires re-machining will be referred to as the "surface condition specification process."

[0013] In this embodiment, the workpiece used to present multiple types of surface information to the user during the surface condition designation process and the workpiece to be actually machined are distinguished and referred to as the workpiece Ka and the workpiece to be machined K. The workpiece Ka and the machined workpiece K may be different, and for example, when machining multiple machined workpieces K, the machined workpiece K to be machined first may be referred to as the workpiece Ka used to present multiple types of surface information to the user.

[0014] The processing system 1 includes a processing device 11, an imaging unit 12 that images the surface of a workpiece K to be processed, a setting device 15 used in the designation process of the surface condition, and a control device 20 that controls the drive of the processing device 11 and the designation process of the surface condition. The setting device 15 includes a display (corresponding to the "presentation unit" according to the present invention) 15A that outputs information on a plurality of surfaces of the workpiece Ka to a user, and an input device (corresponding to the "designation unit" according to the present invention) 15B for the user to perform a designation operation.

[0015] The processing device 11 is, for example, a polishing device that polishes the surface of a workpiece K to be processed. The processing device 11 includes a head unit 11a that performs polishing and a robot arm 11b that moves the head unit 11a, and can polish various locations on the surface of the workpiece K to be processed by moving the head unit 11a to the various locations.

[0016] The photographing unit 12 is a digital camera or the like, and photographs the processing surface of the workpiece K to be processed. The photographing unit 12 only needs to be able to photograph still images, and may be configured to photograph the workpiece K to be processed so that the entire area of ​​the processing surface of the workpiece K fits within one image. Alternatively, the photographing unit 12 may be configured to photograph the workpiece K to be processed so that a portion of the processing surface of the workpiece K fits within one image, and may be configured to be able to change the photographing position (for example, to be attached to the robot arm 11b), and may be configured to be able to photograph the entire area of ​​the processing surface of the workpiece K to be processed by the photographing unit 12 photographing the workpiece K to be processed from various photographing positions.

[0017] The display device 15A is a device capable of outputting an image. The input device 15B is a device, such as a mouse or a keyboard, that allows a user to give instructions and operations to the image displayed and output on the display device 15A.

[0018] The control device 20 is a computer having a CPU (Central Processing Unit), a RAM (Random Access Memory) in which the CPU expands data, a storage device in which a control program executed by the CPU and control data are stored, and an interface for transmitting and receiving data between the CPU and external devices. In the control device 20, a plurality of functional modules are realized by the CPU executing the control program.

[0019] The multiple functional modules include an assistance processing unit 21 that executes a surface condition designation process (a process that allows a user to designate information on a surface that requires reprocessing), an image processing unit 22 that performs image processing on a captured image, a processing control unit 23 that controls the drive of the processing device 11, a reprocessing determination unit 24 that determines a portion that requires reprocessing when processing the workpiece K to be processed, and an AnoGAN processing unit 25 that assists in the process of determining a portion that requires reprocessing. The image processing unit 22 functions as a first image processing unit and a second image processing unit according to the present invention.

[0020] <Unit image> The image processing unit 22, re-machining determination unit, and AnoGAN processing unit 25 of the control device 20 process images (hereinafter referred to as "unit images") obtained by cutting a captured image of the workpiece K to be machined into a predetermined size. The size of the unit image may be set to correspond to the size of a section for inspecting the surface condition of the workpiece K to be machined and determining whether or not to re-machine the workpiece K.

[0021] <Image processing unit> The image processing unit 22 performs coordinate conversion processing and spatial frequency component extraction processing. Fig. 2 is a diagram for explaining an example of image conversion processing executed by the image processing unit, showing an image before conversion (A) and an image after conversion (B). Fig. 3 is a diagram showing an example of a work surface image, an FFT processed image, and an IFFT image processed by the image processing unit.

[0022] The coordinate conversion process is a process of converting the coordinates of a plurality of unit images showing the machining surface of the workpiece K to be machined, photographed by the photographing unit 12, so that the machining marks appearing as curved lines become straight lines. In the coordinate conversion process, the image processing unit 22 first performs image recognition to extract the machining mark lines L1 included in the unit image D1, as shown in FIG. 2(A), for example, and then obtains a coordinate conversion equation for converting the line L1 into a straight line. After that, the image processing unit 22 applies the above coordinate conversion to the original unit image D1, as shown in FIG. 2(B), to obtain a unit image D2 in which the machining mark lines L1 are converted into straight lines. The above coordinate conversion equation is preferably determined with the constraint that the difference between the interval between the machining marks in the image and the actual interval between the machining marks is not enlarged.

[0023] The extraction process of spatial frequency components is performed on a unit image that has been converted into a straight line through the above-mentioned coordinate conversion process if the processing line is curved, and on a unit image that has not been converted into a straight line through the above-mentioned coordinate conversion process if the processing line is not curved.

[0024] The spatial frequency component refers to the stripe pattern that is repeated at a regular interval in the unit image, and the interval corresponds to the frequency. The stripe pattern that is repeated at a regular interval appears in the unit image due to the machining marks (tool marks) left on the machined surface, so the spatial frequency component in the image is an index that represents the interval and size (height of the unevenness) of the machining marks.

[0025] In the extraction process of spatial frequency components, the image processing unit 22 performs FFT (Fast Fourier Transform) processing on the unit images D3 and D4 as shown in FIG. 3 to obtain two-dimensional images F3 and F4 in which spatial frequency components are displayed in a two-dimensional graph. The two-dimensional images F3 and F4 are images showing a two-dimensional graph, with the center point O indicating a zero frequency component, and each point {distance r, angle θ} from the center point O indicating the frequency f and angle θ of the spatial frequency component (striped pattern). The amount of spatial frequency components is represented by the brightness of the two-dimensional images F3 and F4. As an example, the two-dimensional image F3 in FIG. 3 includes two points P1 and P2 with high brightness other than the zero point, indicating that the unit image D3 mainly includes two spatial frequency components. Also, the two-dimensional image F4 in FIG. 3 does not include any points with high brightness other than the zero point, indicating that the unit image D4 does not include a large spatial frequency component. It should be noted that the two-dimensional images F3 and F4 in FIG. 3 are shown with light and dark inverted.

[0026] In the extraction process of spatial frequency components, after the image processing unit 22 acquires the two-dimensional images F3 and F4, it may perform a filter process to extract the bright portions, and then perform IFFT (Inverse Fast Fourier transform) processing on the two-dimensional images F3 and F4 after the filter process. By the IFFT process, unit images D3i and D4i of the workpiece K to be processed in which only the spatial frequency components are prominently extracted can be obtained. As an example, the unit image D3i in FIG. 3 is an image including stripe patterns J1 and J2 of two spatial frequencies corresponding to two points P1 and P2 of the two-dimensional image F3. Therefore, it can be easily determined from the unit image D3i that the original unit image D3 includes two types of processing marks corresponding to the two stripe patterns J1 and J2. Further, the unit image D4i in FIG. 3 is an image that does not include a stripe pattern corresponding to the fact that it does not include a large spatial frequency component other than the zero point. Therefore, it can be easily determined from the unit image D4i that almost no processing marks remain in the original unit image D4.

[0027] <AnoGAN Processing Unit> FIG. 4 is a diagram for explaining the learning process (A) and the determination process (B) executed by the AnoGAN processing unit. Generally, AnoGAN (Anomaly Detection with Generative Adversarial Networks) refers to an anomaly determination in which a machine learning model having a structure called GAN is trained by giving a large number of normal images as training data, and then the image to be determined is given to the trained machine learning model to detect abnormal portions of the image.

[0028] The AnoGAN processing unit 25 of this embodiment includes a machine learning model 25a having a GAN structure constructed in a computer, as shown in Figs. 4(A) and (B). As shown in Fig. 4(A), the machine learning model 25a is given a large number of unit images Dtr cut out from a photographed image Qtr of a normally machined work surface as training data, and has already learned the training data. As shown in Fig. 4(B), when each of a plurality of unit images D6 cut out from a photographed image Q6 of a workpiece K to be machined after machining is given to the machine learning model 25a, the machine learning model 25a extracts an abnormal portion an of each unit image D6 by AnoGAN. The unit images Dtr, which are training data, are selected from unit images of a machined workpiece that does not require remachining, and the machine learning model 25a determines a portion that may require remachining as an abnormal portion an. On the other hand, the determined abnormal portion an may be an abnormality based on other factors, not just a portion that requires remachining. Therefore, when the number (e.g. area) of abnormal points an contained in the unit image D6 is equal to or greater than a certain amount, it can be considered that the possibility that the unit image D6 contains a surface state requiring reprocessing is equal to or greater than a certain amount. On the other hand, when the number of abnormal points an contained in the unit image D6 is less than a certain amount, it can be considered that the possibility that the unit image D6 contains a surface state requiring reprocessing is less than a certain amount.

[0029] The AnoGAN processing unit 25 further includes a sorting processing unit 25b that counts the total amount (e.g., total area) of abnormal areas an determined by the machine learning model 25a for the unit images D6 and compares the total amount of abnormal areas an with a predetermined threshold to sort the unit images D6. The AnoGAN processing unit 25 then sorts the unit images D6 whose comparison result is greater than the threshold as unit images D6a that have a certain or higher probability of being determined to require reprocessing, and the unit images D6 whose comparison result is less than the threshold as unit images D6na that have a less than certain probability of being determined to require reprocessing. The set of unit images D6na corresponds to an example of a first image group according to the present invention. The set of unit images D6a corresponds to an example of a second image group according to the present invention.

[0030] <Support processing unit and surface condition designation processing> Fig. 5 is a flow chart showing a process of designating a surface state requiring re-processing, which is executed by the support processing unit, Fig. 6 is a display image diagram showing an example of a designation screen for designating a surface state requiring re-processing.

[0031] The support processing unit 21 starts the surface condition designation processing of FIG. 5 when, for example, a user performs an operation to start the surface condition designation processing. When the designation processing is started, the support processing unit 21 first notifies the user to prepare a workpiece Ka including a portion that needs re-machining (step S1). Here, the user prepares a workpiece Ka including a sufficiently machined portion and an insufficiently machined portion by applying the processing device 11 in various modes to the workpiece Ka for trial machining. Alternatively, a workpiece Ka that has been subjected to various modes of processing, such as a sufficiently machined portion and an insufficiently machined portion, may be prepared separately. Then, when the user notifies the support processing unit 21 that the workpiece Ka has been placed on the workbench (YES in step S2), the support processing unit 21 drives the photographing unit 12 to photograph the surface of the workpiece Ka (step S3).

[0032] Next, the support processing unit 21 divides the photographed image acquired in step S3 into unit images (step S4), and passes the unit images to the image processing unit 22, which performs the above-mentioned coordinate conversion process, FFT process, and IFFT process on the unit images (steps S5 and S6). By the processes of steps S5 and S6, a plurality of unit images are obtained from which the stripe pattern included in the surface of the workpiece Ka is extracted, as shown in the IFFT image of FIG.

[0033] Next, the support processing unit 21 performs a display process of presenting the unit images obtained in steps S5 and S6 on the screen of the display unit 15A and prompting the user to specify the surface state that requires reprocessing (step S7). More specifically, as shown in FIG. 6, the display unit 15A outputs a list display H1 of the multiple unit images obtained in steps S5 and S6 and a message H2 that prompts the user to specify the one that requires reprocessing from the list. In the example of FIG. 6, the list display H1 includes multiple sets of images, each set including the original unit image Dx, the two-dimensional image Fx after FFT processing, and the unit image Dxi after IFFT processing. Note that the list display H1 may include only the unit image Dxi after IFFT processing, or may include only the two-dimensional image Fx after FFT processing, or may include a combination of these and the unit image Dx before FFT processing.

[0034] Then, the support processing unit 21 judges whether the image designation is complete (step S8), and repeats the judgment in step S8 until the image designation is complete.

[0035] Here, the user can easily identify how fine the processing marks are by paying attention to the information on the spatial frequency components of the processed surface shown in the two-dimensional image Fx after FFT processing or the unit image Dxi after IFFT processing in the list display H1. Then, the user can determine whether each two-dimensional image Fx or unit image Dxi is in a surface state that requires re-processing or does not require re-processing based on the fineness and size of the processing marks (height of unevenness). Here, for example, a case is assumed in which the workpiece K to be processed has rough initial processing marks before processing, and the rough processing marks are removed by processing and other fine processing marks are added. In such a case, the user can determine that the two-dimensional image Fx or unit image Dxi in which the spatial frequency components corresponding to the initial rough processing marks remain is in a surface state that requires re-processing, and that the two-dimensional image Fx or unit image Dxi in which the spatial frequency components corresponding to the rough processing marks remain is in a surface state that does not require re-processing, regardless of whether or not there are spatial frequency components corresponding to fine processing marks. Then, the user designates all images determined to have a surface state requiring reprocessing from the list display H1 by performing an instruction operation via the input device 15B. Then, when the designation is completed by operating the OK button H3 indicating completion, the support processing unit 21 advances the process to the next step.

[0036] Next, when the process proceeds, the support processor 21 compares the designated two-dimensional image Fx or unit image Dxi with the undesignated two-dimensional image Fx or unit image Dxi, and calculates the conditions for determining whether re-machining is necessary, such as what kind of spatial frequency components are included to determine that the surface state requires re-machining (step S9). Specifically, for example, if an image (two-dimensional image Fx or unit image Dxi) containing high spatial frequency components (fine stripes) at a size equal to or larger than a predetermined amount is included in an undesignated image, the support processor 21 determines that the high spatial frequency components are tool eyes that do not require re-machining. Also, for example, if an image containing low spatial frequency components (coarse stripes) at a size equal to or larger than a predetermined amount is included in a designated image, while such an image is not included in an undesignated image, the support processor 21 determines that the low spatial frequency components are tool eyes that require re-machining. Furthermore, if an image containing less than a predetermined amount of the above-mentioned low spatial frequency components is included in the unspecified images, the support processor 21 may calculate a threshold value for the amount of components that determines whether or not reprocessing is required, based on the amount of the low spatial frequency components contained in the image. By such processing, the support processor 21 can determine a condition that, for example, if a specific spatial frequency component is contained in an amount equal to or greater than a threshold, it is a part that requires reprocessing.

[0037] When the condition for determining whether reprocessing is necessary is obtained, the support processing unit 21 passes the condition to the reprocessing determination unit 24 (step S10), and ends the designation process of FIG.

[0038] <Machining control unit, re-machining judgment unit and automatic machining process> 6 is a flowchart showing the automatic machining process executed by the machining control unit and the re-machining determination unit. The automatic machining process is started when the workpiece K to be machined is set on the worktable and a machining start command is input by the user.

[0039] When the automatic machining process is started, the machining control unit 23 generates a movement path of the head unit 11a that performs machining on the machining target surface of the workpiece K (step S21). Here, the movement path may be provided to the machining control unit 23 by a user through direct teaching. Direct teaching corresponds to a method in which a user operates the robot arm 11b to move the head unit 11a along a desired path, thereby causing the machining control unit 23 to memorize the path. In addition, the movement path may be calculated by the user providing the machining control unit 23 with position information and an operation command that determine the movement path, or the machining control unit 23 may calculate a movement path along the machining target surface based on the position detected by detecting the position of the workpiece K.

[0040] Next, the machining control unit 23 drives the head unit 11a while driving the robot arm 11b so that the head unit 11a moves along the generated movement path, thereby performing machining (step S22). By this driving, machining is performed on the machining target surface of the workpiece K to be machined.

[0041] Once the processing is completed, the re-processing determination unit 24 drives the photographing unit 12 to photograph the entire surface of the workpiece K to be processed (step S23). Then, the re-processing determination unit 24 links the photographed image with location data indicating which location of the workpiece K it is, and divides it into a plurality of unit images (step S24).

[0042] Next, the reprocessing determination unit 24 sends multiple unit images to the AnoGAN processing unit 25, and sorts them into unit images that are more than a certain probability that they contain a surface condition that should be determined to require reprocessing, and unit images that are less than a certain probability that they contain a surface condition that should be determined to require reprocessing, based on the amount of detected abnormal areas an (step S25).

[0043] Then, the re-machining judgment unit 24 sends the unit images that are more than a certain possibility of including a surface state that should be judged as requiring re-machining to the image processing unit 22, and causes the image processing unit 22 to perform a coordinate conversion process (step S26) for converting curved machining marks into straight lines, and a process for extracting spatial frequency components contained in the unit images by FFT processing or FFT processing and IFFT processing, and for converting the extracted spatial frequency components into numerical values ​​of frequency and magnitude of the frequency components (step S27). The frequency and magnitude of the frequency components can be obtained by searching for positions of high brightness in the two-dimensional image after FFT processing, and from the positions and brightness. Alternatively, the frequency and magnitude of the frequency components can be obtained by determining the interval of the stripe pattern and the shading ratio of the stripe pattern from the unit images after IFFT processing by image recognition processing.

[0044] Furthermore, the re-processing determination unit 24 applies the values ​​(frequency and magnitude of frequency components) indicating the spatial frequency components extracted in step S27 to the conditions for determining whether or not re-processing is required, which are passed from the support processing unit 21 in the designation process of Fig. 5, to determine whether or not re-processing is required (step S28). Here, the re-processing determination unit 24 performs the above determination process for all unit images that have been subjected to the processes of steps S26 and S27.

[0045] As a result, it is determined whether there is a unit image that is determined to match the condition (requires remachining) (step S29), and if NO, the machining control unit 23 ends the automatic machining process for one workpiece K to be machined. On the other hand, if the determination result in step S29 is YES, the machining control unit 23 generates a movement path for moving the head unit 11a so as to remachine the part of the workpiece K to be machined that is shown in the unit image based on the part data linked to the unit image determined to match (step S30). Then, the machining control unit 23 drives the robot arm 11b while driving the head unit 11a so that the head unit 11a moves according to the generated movement path (step S31). The processing in step S31 applies remachining to the part that requires remachining.

[0046] When the re-machining in which the head unit 11a moves along the path generated in step S30 is completed, the machining control unit 23 and the re-machining determination unit 24 then repeat the process from step S23 until step S29 is determined to be NO (no unit image is determined to meet the condition requiring re-machining). Then, when step S29 is determined to be NO, the automatic machining process for machining one workpiece K to be machined is terminated. Through this automatic machining process, the machining system 1 can machine the workpiece K to be machined until there are no more parts requiring re-machining.

[0047] As described above, according to the machining system 1 of the present embodiment, the support processing unit 21 presents information on a plurality of types of workpiece surfaces to the user, and the user can specify one of the pieces of workpiece surface information using the input device 15B. Then, in the subsequent automatic machining process, the remachining determination unit 24 determines the portion of the workpiece K that requires remachining based on the information obtained from the photographed image of the surface of the workpiece K after machining and the workpiece surface information specified by the user. Therefore, even if there are surface states that require remachining and surface states that do not require remachining, and the distinction between these differs depending on, for example, the product specifications, according to the machining system 1 of the present embodiment, the portion that requires remachining can be appropriately determined and the portion can be controlled so as to be remachined.

[0048] On the surface of the workpiece K to be machined, a pattern in which a similar pattern (e.g., unevenness) is repeated at regular intervals, such as machining marks, may occur, and further, such patterns may have different fineness and different sizes (height of unevenness). Then, it may be required to determine how many patterns of a certain fineness remain in a part, which requires re-machining of the part. Therefore, according to the machining system 1 of this embodiment, information indicating the spatial frequency components of the workpiece surface is applied as information on the workpiece surface presented to the user in the surface condition designation process. By showing the information on the spatial frequency components, it is possible to eliminate shadows in the photograph, patterns such as unevenness that are not repeated, or noise on the image, and to highlight only the information on the pattern in which a similar pattern is repeated at regular intervals, so that the user can recognize it. Therefore, based on the information on the spatial frequency components, the user can accurately distinguish between a surface condition that requires re-machining and a surface condition that does not require re-machining, and can accurately designate them.

[0049] Furthermore, according to the machining system 1 of this embodiment, during automatic machining, the remachining determination unit 24 acquires information on spatial frequency components from the photographed image of the workpiece K to be machined after machining, and compares this information with information on spatial frequency components designated by the user to determine the locations that require remachining. Through such processing, it is possible to detect with high accuracy the locations that require remachining according to the presence or absence or amount of a pattern that is repeated at regular intervals, such as machining marks, and to appropriately perform remachining of the workpiece K to be machined.

[0050] Furthermore, according to the processing system 1 of this embodiment, the image processing unit 22 performs FFT processing or FFT processing and IFFT processing on the captured image (its unit image) to generate information on spatial frequency components contained in the captured image. By searching for points with high brightness contained in the two-dimensional image using the two-dimensional image obtained by FFT processing, it is possible to identify the spatial frequency and the magnitude of its components, and to identify patterns that are repeated at regular intervals, such as processing marks, with high accuracy. In addition, the unit image obtained by IFFT processing allows the user to easily grasp patterns that are repeated at regular intervals, such as processing marks, based on the spacing and shading of the stripes.

[0051] Furthermore, according to the machining system 1 of this embodiment, the image processing unit 22 performs coordinate conversion processing on the captured image (its unit image), thereby converting the machining marks included in the captured image so that they become linear. Therefore, even if the workpiece K to be machined has a curved surface and the machining marks are captured in a curved shape depending on the direction in which the part is photographed, the influence of such a curved surface can be eliminated. As a result, the user can easily and accurately specify the surface state that requires remachining and the surface state that does not require remachining, and the remachining determination unit 24 can determine the part that requires remachining with high accuracy.

[0052] Furthermore, according to the machining system 1 of this embodiment, the AnoGAN processing unit 25 divides the photographed image (plurality of unit images D6) of the workpiece K to be machined into unit images D6a whose abnormality determination area is equal to or greater than the threshold, and unit images D6na whose abnormality determination area is less than the threshold. Furthermore, the re-machining determination unit 24 does not determine whether re-machining is necessary for one of the divided unit images D6na, but determines whether re-machining is necessary for the other divided unit image D6a. Therefore, the number of unit images on which the re-machining determination unit 24 performs the determination process can be reduced, thereby reducing the load on the re-machining determination unit 24 and speeding up the process of determining whether re-machining is necessary.

[0053] The above describes the embodiments of the present invention. However, the present invention is not limited to the above embodiments. For example, in the above embodiment, the control device 20 controls the processing device 11 to automatically perform processing and re-processing on the workpiece K to be processed. However, the processing and re-processing may be performed by an operator operating the robot arm 11b, or may be performed manually by an operator. In this case, the processing control unit 23 is removed from the control device 20 in FIG. 1. Also, a configuration in which the processing control unit 23 and the processing device 11 are removed from the processing system 1 constitutes an example of a processing support device E according to the present invention.

[0054] In the above embodiment, the support processing unit 21 presents the user with a two-dimensional image that has been FFT-processed or a unit image that has been IFFT-processed in the surface condition designation process. However, when the two-dimensional image that has been FFT-processed contains a plurality of spatial frequency components, or when the unit image that has been IFFT-processed contains a plurality of spatial frequency components, the image may be divided into individual spatial frequency components and presented to the user. For example, when the two-dimensional image that has been FFT-processed has a luminance peak at the first point P1 and the second point P2, the image may be divided into two images, one in which the peak at the first point P1 is left and the peak at the second point P2 is excluded, and the other in which the peak at the first point P1 is excluded and the peak at the second point P2 is left, and presented to the user. Alternatively, IFFT processing may be performed on each of the two images thus divided, and two unit images obtained by the processing (a unit image in which a striped pattern corresponding to the peak at the first point P1 appears, and a unit image in which a striped pattern corresponding to the peak at the second point P2 appears) may be presented to the user. In the above embodiment, the support processing unit 21 includes a configuration in which the user specifies the surface state requiring reprocessing, but the support processing unit 21 may already hold information on the surface state requiring reprocessing in advance, or may hold the information by specification or learning prior to that point in time, and in this case, the support processing unit 21 may not have a configuration in which an image is presented to prompt the user to specify the surface state.

[0055] In the above embodiment, the processing system for polishing has been described, but the processing system according to the present invention is not limited to polishing, and can be applied to systems for performing various processes such as cutting, grinding, and special processes for processing the surface of a workpiece using discharge, laser irradiation, or electrolytic action. In the above embodiment, a configuration was shown in which a process for extracting spatial frequency components of a photographed image (extracting striped processing marks) is incorporated into a process for specifying a surface state and a process for determining whether or not reprocessing is required, taking as an example a polishing process in which striped processing marks are a material for determining whether or not reprocessing is required. However, a process suitable for incorporating a process for extracting spatial frequency components of a photographed image is not limited to polishing, and for example, if a surface state in which a similar pattern appears repeatedly at a predetermined interval, such as a cutting process in which burrs are generated at approximately equal intervals, is a material for determining whether or not reprocessing is required, incorporating a process for extracting spatial frequency components of a photographed image is useful as in the above embodiment.

[0056] In the above embodiment, the surface condition designation process is described as a process in which the user designates surface information that requires reprocessing, but the process may be a process in which the user designates surface information that does not require reprocessing. In addition, the coordinate change process for converting curved processing marks in the captured image into straight lines, the distribution process of the captured image by AnoGAN, or both of these may be omitted. In addition, in the above embodiment, a configuration in which information on spatial frequency components extracted from the captured image is presented to the user in the surface condition designation process is shown, but the information on the work surface presented to the user may be a captured image showing the processed state as it is, or may be an image from which shadows and noise on the image have been removed. In addition, the details shown in the embodiment can be appropriately changed within the scope of the invention. [Explanation of symbols]

[0057] 1 Processing system E Processing support equipment 11 Processing equipment 11a Head section 11b Robot arm 12. Photography Department 15 Setting device 15A Display (presentation part) 15B Input device (designated part) 20 Control device 21 Support Processing Unit 22 Image processing section 23 Processing control section 24 Rework judgment section 25 AnoGAN processing section 25a Machine Learning Models 25b Distribution processing unit K Workpiece to be processed D3, D4 unit image (photographed image) F3, F4 2D image (image after FFT processing) D3i, D4i unit images (images after IFFT processing) H1 List View

Claims

1. A presentation unit that presents information on a plurality of types of work surfaces; A designation unit capable of externally designating one of the multiple types of work surface information presented by the presentation unit; An imaging unit for acquiring an image of a workpiece to be processed after the workpiece is processed; a re-machining determination unit that determines a portion of the workpiece that needs to be re-machined based on information designated by the designation unit and information obtained from the captured image; Equipped with The information designated by the designation unit is designated as information indicating a surface condition requiring reprocessing, A machining support device, wherein the information on the workpiece surface presented by the presentation unit is information indicating spatial frequency components of the workpiece surface.

2. A presentation unit that presents information on a plurality of types of work surfaces; A designation unit capable of externally designating one of the multiple types of work surface information presented by the presentation unit; An imaging unit for acquiring an image of a workpiece to be processed after the workpiece is processed; a re-machining determination unit that determines a portion of the workpiece that needs to be re-machined based on information designated by the designation unit and information obtained from the captured image; Equipped with The information designated by the designation unit is designated as information indicating a surface condition requiring reprocessing, A processing support device, wherein the information obtained from the captured image is information indicating the spatial frequency components of the workpiece surface in the captured image.

3. A presentation unit that presents information on a plurality of types of work surfaces; A designation unit capable of externally designating one of the multiple types of work surface information presented by the presentation unit; An imaging unit for acquiring an image of a workpiece to be processed after the workpiece is processed; a re-machining determination unit that determines a portion of the workpiece that needs to be re-machined based on information designated by the designation unit and information obtained from the captured image; Equipped with The information designated by the designation unit is designated as information indicating a surface condition requiring reprocessing, The photographing unit acquires the photographed images of a plurality of locations of the workpiece to be machined, The image processing device further includes an AnoGAN processing unit that divides the captured images of the plurality of locations into a first image group and a second image group having a larger number of areas detected as abnormal than the first image group by AnoGAN, the re-processing determination unit does not determine a portion of the captured images of the first image group that requires re-processing, and determines a portion of the captured images of the second image group that requires re-processing. Processing support equipment.

4. An imaging unit for acquiring an image of a workpiece to be processed after the workpiece is processed; a re-machining determination unit that determines a portion of the workpiece that requires re-machining based on information indicating a surface state that requires re-machining and information obtained from the captured image; Equipped with A processing support device, wherein the information obtained from the captured image is information indicating the spatial frequency components of the workpiece surface in the captured image.

5. An imaging unit for acquiring an image of a workpiece to be processed after the workpiece is processed; a re-machining determination unit that determines a portion of the workpiece that requires re-machining based on information indicating a surface state that requires re-machining and information obtained from the captured image; Equipped with The photographing unit acquires the photographed images of a plurality of locations of the workpiece to be machined, The image processing device further includes an AnoGAN processing unit that divides the captured images of the plurality of locations into a first image group and a second image group having a larger number of areas detected as abnormal than the first image group by AnoGAN, The re-processing determination unit does not determine the locations of the captured images in the first image group that require re-processing, but determines the locations of the captured images in the second image group that require re-processing.

6. A first image processing unit performs FFT or FFT and IFFT processing on the captured image, information indicating the spatial frequency components is generated by the processing of the first image processing unit; The machining support device according to claim 2 or 4.

7. A second image processing unit performs coordinate conversion so that curved processing marks included in the captured image become straight lines, The first image processing unit performs the processing on the image that has been coordinate-transformed by the second image processing unit. The machining support device according to claim 6.

8. A processing device that performs processing; The machining support device according to any one of claims 1 to 7, A processing system comprising:

Images