Measuring device, additive processing system and cutting processing system

Abstract

This measurement device (10) comprises: a sensor (12) for acquiring image information by imaging an object for which addition or cutting of a material is to be implemented; a measurement unit (13) for measuring the shape of the object on the basis of the image information, thereby acquiring measurement data indicating the shape of the object; a deficient region detection unit (15) for detecting a deficient region, which is a region on the object for which the measurement data is deficient; a measurement data supplementation unit (16) for re-measuring the shape of the object on the basis of image data acquired through an additional instance of imaging by the sensor (12), thereby acquiring re-measurement data pertaining to the deficient region, and supplementing the measurement data using the re-measurement data; and a machining region identification unit (17) for identifying, on the basis of the supplemented measurement data and a model of a completed component produced through addition or cutting, a machining region in which addition or cutting is to be implemented.

Description

[Technical field]

[0001] The present disclosure relates to a measurement apparatus, an additive machining system, and a cutting machining system that measure an object to which material is added or removed. [Background technology]

[0002] When processing an object by adding material to it or by cutting it, the processing area of ​​the object to be added or cut is specified by measuring the shape of the object. In order to specify the processing area, 3D measurement data of the object is required.

[0003] Patent Document 1 discloses a processing device that machines a tool by removing material, and discloses that when the processing device remachines a used and damaged tool, a measurement unit of the processing device uses a sensor to perform 3D measurement of the contour of the tool and obtain 3D measurement data of the tool. The measurement unit identifies a processing area of ​​the tool from which material is to be removed based on the difference between a tool model formed based on the 3D measurement data and a preset reference contour. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Special Publication No. 2018-516178 Summary of the Invention [Problem to be solved by the invention]

[0005] In the measurement for identifying the processing area, depending on the shape or size of the object, measurement omissions may occur due to blind spots when detecting the shape of the object. When measurement omissions occur, it becomes difficult to accurately identify the processing area. The technology of the above-mentioned Patent Document 1 does not take into consideration measurement omissions due to blind spots, so there is a problem that it becomes difficult to accurately identify the processing area depending on the object.

[0006] The present disclosure has been made in consideration of the above, and aims to provide a measuring device that makes it possible to accurately identify a processing area to be added or removed from an object to which material is to be added or removed. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems and achieve the objective, the measuring device disclosed herein comprises a sensor that acquires image information by capturing an image of an object to which material is to be added or cut, a measurement unit that acquires measurement data indicating the shape of the object by measuring the shape of the object based on the image information, a missing area detection unit that detects a missing area which is an area of ​​the object where measurement data is missing, a measurement data complementation unit that acquires re-measurement data which is measurement data for the missing area by re-measuring the shape of the object based on the image information acquired by re-capturing the image of the sensor and complements the measurement data with the re-measurement data, and a processing area identification unit that identifies the processing area to be added or cut based on a model of the finished product resulting from addition or cutting and the complemented measurement data. The missing area detection unit includes a missing candidate point detection unit that detects missing candidate points, which are candidates for points included in the contour of the missing area, from the measurement data acquired by the measurement unit; a contour extraction unit that extracts a contour including the missing candidate points from the missing candidate point data; an area calculation unit that calculates the area of ​​the area enclosed by the contour; and a missing area determination unit that determines whether the area enclosed by the contour is a missing area based on the calculated area. Effect of the Invention

[0008] The measuring device according to the present disclosure has an effect of making it possible to accurately identify a processing area to which material is to be added or removed from an object to which material is to be added or removed. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram showing a functional configuration of a measurement device according to a first embodiment; [Diagram 2] FIG. 1 is a diagram showing an example of a hardware configuration for implementing a processing unit of a measuring device according to a first embodiment; [Diagram 3] 1 is a first flowchart showing a procedure of a process performed by the measuring device according to the first embodiment; [Figure 4] 2 is a second flowchart showing a procedure of a process performed by the measuring device according to the first embodiment; [Diagram 5] FIG. 13 is a diagram showing a configuration example of a missing area detection unit included in a measurement device according to a second embodiment; [Figure 6] FIG. 13 is a diagram showing a configuration example of a measurement data complementing unit included in a measurement device according to a second embodiment; [Figure 7] 11 is a flowchart showing a procedure of processing by a missing area detection unit and a measurement data complementation unit included in the measurement device according to the second embodiment. [Figure 8] FIG. 13 is a diagram showing a configuration example of a measurement condition setting unit included in a measurement device according to a third embodiment; [Figure 9] 11 is a flowchart showing a procedure of a process performed by a measurement condition setting unit included in the measurement apparatus according to the third embodiment. [Figure 10] FIG. 13 is a diagram showing a configuration example of a range adjustment unit included in a measurement condition setting unit according to a third embodiment; [Figure 11] FIG. 13 is a diagram showing a configuration example of a measurement distance adjustment unit included in a measurement condition setting unit according to a third embodiment; [Figure 12] FIG. 13 is a diagram showing a configuration example of an exposure time adjustment unit included in a measurement condition setting unit in the third embodiment; [Figure 13] 11 is a flowchart showing a procedure of processing by a range adjustment unit, a measurement distance adjustment unit, and an exposure time adjustment unit included in the measurement device according to the third embodiment. [Figure 14] FIG. 13 is a diagram showing a configuration example of a processing region specifying unit included in a measurement device according to a fourth embodiment; [Figure 15] 13 is a first flowchart showing a procedure of a process performed by a processing region specifying unit included in the measurement apparatus according to the fourth embodiment; [Figure 16] 20 is a second flowchart showing a procedure of a process performed by the processing area specifying unit included in the measurement apparatus according to the fourth embodiment; [Figure 17] FIG. 13 is a diagram showing a configuration example of an additional processing system according to a fifth embodiment. [Figure 18] 11 is a flowchart showing an operation procedure of the additive processing system according to the fifth embodiment. [Figure 19] FIG. 13 is a diagram showing a configuration example of a cutting processing system according to a sixth embodiment. [Figure 20]13 is a flowchart showing an operation procedure of the cutting system according to the sixth embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] A measuring device, an additional machining system, and a cutting system according to embodiments will be described in detail below with reference to the drawings.

[0011] Embodiment 1 1 is a diagram showing a functional configuration of a measuring device 10 according to a first embodiment. The measuring device 10 measures the shape of an object to which material is to be added or cut, thereby identifying a processing area in the object. The processing area is an area of ​​the object to which material is to be added or cut. In the following description, the processing area to which material is added is referred to as an adding area, and the processing area to which material is to be cut is referred to as a cutting area.

[0012] The measuring device 10 includes a measurement condition setting unit 11 that sets measurement conditions, a sensor 12 that captures an image of an object, a measuring unit 13 that measures the shape of the object, and a storage unit 18 that stores various information. The measuring device 10 also includes a measurement data integration unit 14, a missing area detection unit 15, a measurement data complementation unit 16, and a processing area specification unit 17.

[0013] The sensor 12 acquires image information by capturing an image of an object. The sensor 12 is a 2D camera or a 3D sensor. The image information acquired by the sensor 12 is 2D data such as a gray image or a color image, or 3D data such as a three-dimensional point cloud data or a range image. The sensor 12 may be, for example, two 2D laser scanners. The 3D data may be acquired by arranging the two 2D laser scanners alternately in a cross shape. The two 2D laser scanners alternately arranged in a cross shape refers to arranging the two 2D laser scanners so that the scanning plane of one 2D laser scanner and the scanning plane of the other 2D laser scanner are perpendicular to each other. In the following description, the measurement device 10 acquires 3D data to measure an object.

[0014] The measurement condition setting unit 11 sets the measurement conditions for measurement by the measurement unit 13. The measurement conditions include an installation range, a measurement distance, an observation angle, and an exposure time. The installation range is a range in which the object and the sensor 12 can be set when image information is acquired. The measurement distance is the distance from the object to the sensor 12. The observation angle is an angle representing the direction of the sensor 12 based on the object. The exposure time is the exposure time of the sensor 12 at the time of image capture. The measurement condition setting unit 11 sets the measurement conditions according to the state of the object. Note that the measurement conditions are not limited to those described in the first embodiment. The measurement conditions may be any conditions necessary for measurement and may be arbitrary.

[0015] The measurement condition setting unit 11 sets the measurement conditions by actually measuring the object using the sensor 12. Alternatively, the measurement condition setting unit 11 sets the measurement conditions by simulation. When setting the measurement conditions by simulation, the measurement condition setting unit 11 sets the measurement conditions by placing the sensor 12 and the object in a virtual space and simulating a scene when the object is imaged by the sensor 12. The measurement condition setting unit 11 reads out a first reference model indicating the shape of the object from the storage unit 18 and places the first reference model in the virtual space. The first reference model is stored in advance in the storage unit 18.

[0016] The measurement unit 13 acquires measurement data indicating the shape of the object by measuring the shape of the object based on the image information. The measurement data is 2D data or 3D data. The object is placed on a rotation stage that can rotate around an A axis and a B axis, for example. The A axis and the B axis are two rotation axes that are perpendicular to each other.

[0017] The measurement unit 13 changes the orientation of the object by rotating the object using a rotation stage. The measurement unit 13 measures the shape of the object by having the sensor 12 capture an image of the object while changing the orientation of the object. When a controller such as a numerical control device controls the rotation stage in cooperation with the sensor 12, the measurement unit 13 automatically measures the object.

[0018] The measurement unit 13 measures the shape of the object by changing the relative position of the object with respect to the sensor 12 or the relative orientation of the object with respect to the sensor 12. That is, the measurement unit 13 measures the object by changing at least one of the position of the object, the orientation of the object, the position of the sensor 12, and the orientation of the sensor 12. The direction in which the position of the object is changed and the direction in which the position of the sensor 12 is changed can be any of the X-axis direction, the Y-axis direction, and the Z-axis direction. The X-axis, the Y-axis, and the Z-axis are three axes perpendicular to each other.

[0019] The object may be grasped by a robot arm and rotated by the movement of the arm. Alternatively, the sensor 12 may be attached to the robot arm and the position or attitude of the sensor 12 may be changed by the movement of the arm. The device that changes at least one of the position of the object, the attitude of the object, the position of the sensor 12, and the attitude of the sensor 12 is not limited to a rotation stage or a robot, and may be another device.

[0020] The measurement data integration unit 14 integrates the measurement data acquired at different times by the measurement unit 13. For example, the measurement data integration unit 14 calculates the center position of the rotating stage and integrates the measurement data acquired based on the center position. When the measurement data acquired by the measurement unit 13 includes unnecessary data, for example data about the background of the object, the measurement data integration unit 14 may delete the unnecessary background data using a background subtraction method. In this way, the measurement data integration unit 14 may integrate only the measurement data about the object.

[0021] The missing area detection unit 15 detects missing areas based on the measurement data integrated by the measurement data integration unit 14. A missing area is an area of ​​the object where measurement data is missing. Depending on the shape or size of the object, measurement gaps may occur due to blind spots of the sensor 12. Measurement data is missing due to measurement gaps.

[0022] For example, the missing area detection unit 15 detects the missing area by extracting the contour of the object from the three-dimensional point cloud data, which is the measurement data, and comparing the extracted contour with the contour of a second reference model. The second reference model is a model of a finished product obtained by adding or cutting. The second reference model is set in advance in the measurement device 10. The missing area detection unit 15 may perform statistical processing of the three-dimensional point cloud data and detect the missing area based on the statistical value.

[0023] The measurement data complementing unit 16 acquires remeasurement data, which is measurement data for the missing area, by re-measuring the shape of the object based on image information acquired by re-imaging the sensor 12, and complements the measurement data with the remeasurement data. If the position of the missing area or the orientation of the object when the missing area faces the sensor 12 is known by detection of the missing area by the missing area detection unit 15, the measurement data complementing unit 16 may change the position or orientation of the object to match the known position or orientation and perform remeasurement. The measurement data complementing unit 16 may perform remeasurement by increasing the variation of the position or orientation of the object compared to the case of measurement by the measurement unit 13. The measurement data complementing unit 16 may perform remeasurement by increasing the variation of the position or orientation of the sensor 12 compared to the case of measurement by the measurement unit 13.

[0024] The missing area detection unit 15 confirms that there is no missing area in the measurement data complemented by the measurement data complementing unit 16. If a missing area is detected again by the missing area detection unit 15, the measurement data complementing unit 16 performs remeasurement again and complements the measurement data. When it is confirmed that there is no missing area, the measurement data complementing unit 16 outputs the measurement data.

[0025] The machining area specifying unit 17 specifies the added area or the cut area, which is the machining area, based on the second reference model and the supplemented measurement data. The reference model is stored in advance in the storage unit 18. The reference model is a three-dimensional model or a two-dimensional model. The machining area specifying unit 17 compares the reference model read from the storage unit 18 with the measurement data.

[0026] When identifying an additional area, the machining area identifying unit 17 superimposes the measurement data on the reference model and identifies an area that is present in the reference model but not in the measurement data as an additional area. When identifying a cutting area, the machining area identifying unit 17 superimposes the measurement data on the reference model and identifies an area that is present in the measurement data but not in the reference model as a cutting area. The machining area identifying unit 17 may identify an additional area or a cutting area by other methods.

[0027] Next, a hardware configuration for realizing the processing unit of the measuring device 10 will be described. Fig. 2 is a diagram showing an example of a hardware configuration for realizing the processing unit of the measuring device 10 according to the first embodiment. The processing units of the measuring device 10, that is, the measurement condition setting unit 11, the measuring unit 13, the measurement data integration unit 14, the missing area detection unit 15, the measurement data complementation unit 16, and the processing area specification unit 17, are realized by using a processing circuit 80. The processing circuit 80 has a processor 82 and a memory 83.

[0028] The processor 82 is a central processing unit (CPU). The processor 82 may be an arithmetic unit, a microprocessor, a microcomputer, or a digital signal processor (DSP). The memory 83 is, for example, a random access memory (RAM), a read only memory (ROM), a flash memory, an erasable programmable read only memory (EPROM), or an electrically erasable programmable read only memory (EEPROM (registered trademark)).

[0029] The memory 83 stores a program for operating as the processing unit of the measuring device 10. The processing circuit 80 can realize the function of the processing unit by having the processor 82 read and execute the program. The input unit 81 is a circuit that receives an input signal to the processing unit of the measuring device 10. Image information from the sensor 12 is input to the input unit 81. The output unit 84 is a circuit that outputs a signal generated by the processing unit of the measuring device 10. The output unit 84 outputs data indicating the identified processing area.

[0030] 2 is an example of hardware in which the processing unit of the measuring device 10 is realized by a general-purpose processor 82 and memory 83, but the processing unit of the measuring device 10 may be realized by a dedicated processing circuit instead of the processor 82 and memory 83. The dedicated processing circuit is a single circuit, a composite circuit, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a circuit that combines these. Note that a part of the processing unit may be realized by the processor 82 and memory 83, and the remaining part may be realized by a dedicated processing circuit.

[0031] Next, a description will be given of the processing performed by the measuring device 10. Fig. 3 is a first flowchart showing the procedure of the processing performed by the measuring device 10 according to the first embodiment. Fig. 3 shows the procedure of the processing performed when the measuring device 10 identifies an additional region.

[0032] In step S1, the measurement device 10 sets measurement conditions by the measurement condition setting unit 11. The measurement condition setting unit 11 sets measurement conditions such as an installation range, a measurement distance, an observation angle, and an exposure time according to the state of the object.

[0033] The measuring device 10 acquires image information by the sensor 12 capturing an image of an object. In step S2, the measurement unit 13 of the measuring device 10 measures the shape of the object based on the image information and acquires measurement data. In step S3, the measuring device 10 integrates the measurement data by the measurement data integration unit 14. The measurement data integration unit 14 integrates the measurement data acquired by capturing images multiple times.

[0034] In step S4, the missing area detection unit 15 of the measuring device 10 detects a missing area based on the measurement data integrated in step S3. In step S5, the measurement data complementation unit 16 of the measuring device 10 re-measures the shape of the object and complements the measurement data. In step S6, the processing area identification unit 17 of the measuring device 10 identifies an additional area based on the measurement data complemented in step S5. With the above, the measuring device 10 ends the processing according to the procedure shown in FIG. 3.

[0035] Fig. 4 is a second flowchart showing the procedure of processing by the measuring device 10 according to the first embodiment. Fig. 4 shows the procedure of processing when the measuring device 10 identifies the cutting area. The procedures from step S1 to step S5 shown in Fig. 4 are similar to the procedures from step S1 to step S5 shown in Fig. 3. After completing step S5 shown in Fig. 4, the measuring device 10 advances the procedure to step S7.

[0036] In step S7, the machining area specifying unit 17 of the measuring device 10 specifies the cutting area based on the measurement data complemented in step S5. With the above, the measuring device 10 ends the processing according to the procedure shown in FIG.

[0037] According to the first embodiment, the measuring device 10 detects a missing area of ​​an object, which is an area where measurement data is missing. The measuring device 10 obtains remeasurement data for the missing area by re-measuring the shape of the object based on image information acquired by re-imaging the sensor 12, and complements the measurement data with the remeasurement data. By complementing the measurement data, the measuring device 10 becomes able to accurately identify the processing area for objects of various shapes or sizes.

[0038] As described above, the measuring device 10 has an effect of being able to accurately identify a processing area to which material is to be added or cut on an object to which material is to be added or cut. The measuring device 10 is suitable for processing complex parts, and can be used, for example, for processing vehicle parts, aviation parts such as turbines, or space parts. The measuring device 10 can improve the efficiency of the setup work for identifying the adding area or cutting area. The measuring device 10 can shorten the time required for the setup work, and can reduce the cost required for the setup work.

[0039] Embodiment 2 In the second embodiment, a configuration example of missing area detection unit 15 and a configuration example of measurement data complementation unit 16 will be described. Fig. 5 is a diagram showing a configuration example of missing area detection unit 15 included in measurement apparatus 10 according to the second embodiment. Missing area detection unit 15 includes a missing area candidate point detection unit 21, a contour extraction unit 22, an area calculation unit 23, and a missing area determination unit 24.

[0040] The missing candidate point detection unit 21 detects missing candidate points from the measurement data acquired by the measurement unit 13. Missing candidate points are candidates for points included in the contour of a missing area. The missing candidate point detection unit 21 detects missing candidate points from three-dimensional point cloud data, which is measurement data. The missing candidate point detection unit 21 determines a point of interest from the three-dimensional point cloud data. The missing candidate point detection unit 21 calculates an angle between a vector from the point of interest to a first neighboring point and a vector from the point of interest to a second neighboring point for neighboring points, which are each point around the point of interest in the point cloud. The missing candidate point detection unit 21 calculates an angle θ expressed by the following formula (1), with the vector from the point of interest to the first neighboring point being (a1, a2, a3) and the vector from the point of interest to the second neighboring point being (b1, b2, b3).

[0041]

number

[0042] The missing candidate point detection unit 21 generates a histogram of the calculated angle θ. When the histogram is distributed around an angle larger than a certain reference angle, the missing candidate point detection unit 21 determines that the attention point is a missing candidate point. When the histogram is distributed around an angle smaller than the reference angle, the missing candidate point detection unit 21 determines that the attention point is not a missing candidate point. The missing candidate point detection unit 21 detects missing candidate points from the three-dimensional point cloud data by determining whether or not all points in the three-dimensional point cloud data are missing candidate points. The missing candidate point detection unit 21 may change the reference angle depending on the shape of the object. The method of detecting missing candidate points is not limited to the method described in the second embodiment, and may be any method.

[0043] The contour extraction unit 22 extracts a contour including the loss candidate points from the data of the loss candidate points. For example, the contour extraction unit 22 extracts the contour by projecting the loss candidate points onto a certain plane and performing edge extraction using the Canny method or the like. The contour extraction unit 22 may extract the contour by extending the Canny method to three dimensions and performing edge extraction from 3D data. Note that the method of extracting the contour including the loss candidate points is not limited to the method described in the second embodiment and may be any method.

[0044] Area calculation unit 23 calculates the area of ​​the region surrounded by the contour extracted by contour extraction unit 22. Area calculation unit 23 calculates the area by, for example, projecting the contour onto a certain plane and performing a labeling process on the region surrounded by the contour. Note that the method of calculating the area of ​​the region surrounded by the contour is not limited to the method described in the second embodiment and may be any method.

[0045] The defect determination unit 24 determines whether or not the area surrounded by the contour extracted by the contour extraction unit 22 is a defect area based on the area calculated by the area calculation unit 23. The defect determination unit 24 compares the calculated area with a preset threshold value to determine whether or not the area is a defect area. If the calculated area is equal to or greater than the threshold value, the defect determination unit 24 determines that the area surrounded by the contour is a defect area, and outputs the area surrounded by the contour as a defect area. If the calculated area is less than the threshold value, the defect determination unit 24 determines that the area surrounded by the contour is not a defect area. Note that the defect determination unit 24 may change the area threshold value depending on the shape of the object. In addition, the method of determining whether or not the area is a defect area is not limited to the method described in the second embodiment, and may be any method.

[0046] 6 is a diagram illustrating an example of the configuration of the measurement data complementing unit 16 included in the measuring apparatus 10 according to the embodiment 2. The measurement data complementing unit 16 includes a normal distribution calculating unit 25, a position and orientation calculating unit 26, a re-measurement unit 27, and a re-integration unit 28.

[0047] The normal distribution calculation unit 25 calculates a normal distribution, which is a distribution of the directions of normals in the missing area detected by the missing area detection unit 15. For example, the normal distribution calculation unit 25 determines a center point in the missing area and connects the center point with two points among multiple points on the contour to obtain a triangular surface. The normal distribution calculation unit 25 estimates a plane that is a triangular surface. For example, when the missing area is expressed by a rectangle, four triangular surfaces are obtained. The plane is expressed by the following formula (2).

[0048]

number

[0049] According to formula (2), the normal vector of a triangular surface is expressed as (a, b, c). The normal distribution calculation unit 25 can obtain (a, b, c) as parameters representing normals for a plurality of triangular surfaces, and calculate the normal distribution based on the obtained parameters. Note that the method of calculating the normal distribution is not limited to the method described in the second embodiment, and may be any method.

[0050] The position and orientation calculation unit 26 calculates the position or orientation of the object or the position or orientation of the sensor 12 such that the sensor 12 faces the object based on the normal distribution. For example, the position and orientation calculation unit 26 obtains a normal having a frequency equal to or greater than a preset threshold among normals in the missing area. The position and orientation calculation unit 26 calculates the position or orientation of the object or the position or orientation of the sensor 12 such that the direction of the optical axis of the sensor 12 is close to the direction of the obtained normal. Note that the method of calculating the position or orientation of the object or the position or orientation of the sensor 12 such that the sensor 12 faces the object is not limited to the method described in the second embodiment, and may be any method. Here, "the sensor 12 faces the object" does not necessarily mean that the object and the sensor 12 face each other directly. It is sufficient that the missing area detected by the missing area detection unit 15 is included in the area that can be acquired by the sensor 12, and the object and the sensor 12 do not have to face each other directly. "The sensor 12 faces the object" includes cases where the object and the sensor 12 do not face each other directly from the front.

[0051] Remeasurement unit 27 remeasures the shape of the object based on image information acquired by re-imaging sensor 12 after the position or orientation of the object, or the position or orientation of sensor 12 has been corrected. Remeasurement unit 27 performs remeasurement by correcting at least one of the position of the object, the orientation of the object, the position of sensor 12, and the orientation of sensor 12 based on the calculation result by position and orientation calculation unit 26. Remeasurement unit 27 acquires remeasurement data for the missing area by remeasuring the shape of the object.

[0052] The reintegration unit 28 integrates the remeasurement data acquired by the remeasurement unit 27 with the measurement data acquired by the measurement unit 13. When the remeasurement data includes unnecessary data, for example, data about the background of the object, the reintegration unit 28 may delete the unnecessary background data using a background subtraction method. In this way, the reintegration unit 28 may integrate only the remeasurement data about the object into the measurement data.

[0053] The reintegration unit 28 calculates a completion rate that indicates the proportion of the missing area that is completed by the measurement data when the remeasurement data is integrated into the measurement data. When the calculated completion rate exceeds a preset threshold, the measurement device 10 completes the completion of the measurement data by the measurement data completion unit 16. When the calculated completion rate does not exceed the threshold, the measurement device 10 repeats the detection of the missing area by the missing area detection unit 15 and the completion of the measurement data by the measurement data completion unit 16.

[0054] Next, a description will be given of the processing performed by the missing area detection unit 15 and the measurement data complementation unit 16. Fig. 7 is a flowchart showing the procedure of the processing performed by the missing area detection unit 15 and the measurement data complementation unit 16 included in the measuring device 10 according to the second embodiment.

[0055] In step S11, missing area candidate point detection unit 21 of missing area detection unit 15 detects missing area candidate points from the 3D point cloud data, which is the measurement data. In step S12, contour extraction unit 22 of missing area detection unit 15 extracts contours including the missing area candidate points detected in step S11. In step S13, area calculation unit 23 of missing area detection unit 15 calculates the area of ​​the region surrounded by the contours extracted in step S12.

[0056] In step S14, loss determination section 24 of loss area detection section 15 determines whether the area surrounded by the contour is a loss area. Loss determination section 24 determines whether the area is a loss area by comparing the calculated area with a preset threshold value. If it is determined that the area surrounded by the contour is not a loss area (step S14, No), loss area detection section 15 and measurement data complementation section 16 end the processing according to the procedure shown in FIG. 7. On the other hand, if it is determined that the area surrounded by the contour is a loss area (step S14, Yes), loss area detection section 15 and measurement data complementation section 16 proceed to step S15.

[0057] In step S15, normal distribution calculation unit 25 of measurement data complementation unit 16 calculates the normal distribution of the missing region. In step S16, position and orientation calculation unit 26 of measurement data complementation unit 16 calculates the position or orientation of the object or the position or orientation of sensor 12 such that sensor 12 faces the object.

[0058] In step S17, the remeasurement unit 27 of the measurement data complementing unit 16 corrects the position or orientation of the object, or the position or orientation of the sensor 12, remeasures the shape of the object, and acquires remeasurement data. In step S18, the reintegration unit 28 of the measurement data complementing unit 16 integrates the remeasurement data acquired in step S17 into the measurement data.

[0059] In step S19, the reintegration unit 28 determines whether the completion rate of the measurement data exceeds the threshold. If the completion rate of the measurement data does not exceed the threshold (step S19, No), the missing area detection unit 15 and the measurement data completion unit 16 return the procedure to step S11 and repeat the detection of the missing area and the completion of the measurement data. On the other hand, if the completion rate of the measurement data exceeds the threshold (step S19, Yes), the missing area detection unit 15 and the measurement data completion unit 16 end the process according to the procedure shown in FIG. 7.

[0060] According to the second embodiment, the missing area detection unit 15 detects a missing candidate point and extracts a contour including the missing candidate point. The missing area detection unit 15 can detect a missing area by determining whether or not the area surrounded by the contour is a missing area based on the area of ​​the area surrounded by the contour. In addition, the measurement data complementation unit 16 calculates the normal distribution of the missing area and calculates the position or orientation of the object or the position or orientation of the sensor 12 such that the sensor 12 faces the object. The measurement data complementation unit 16 acquires remeasurement data by remeasurement of the object after the position or orientation of the object or the position or orientation of the sensor 12 is corrected, and integrates the remeasurement data into the measurement data. In this way, the measurement device 10 can complement the measurement data for the missing area. As a result, the measurement device 10 has an effect of being able to accurately identify the processing area where the material is added or cut for the object to be added or cut.

[0061] Embodiment 3 In the third embodiment, a configuration example of the measurement condition setting unit 11 will be described. Fig. 8 is a diagram showing a configuration example of the measurement condition setting unit 11 included in the measurement device 10 according to the third embodiment. The measurement condition setting unit 11 includes a range adjustment unit 31, a measurement distance adjustment unit 32, and an exposure time adjustment unit 33.

[0062] The range adjustment unit 31 adjusts an installation possible range, which is a range in which the object and the sensor 12 can be installed when image information is acquired. The measurement distance adjustment unit 32 adjusts the measurement distance of the sensor 12. The measurement distance is the distance from the sensor 12 to the object. The exposure time adjustment unit 33 adjusts the exposure time of the sensor 12 when image information is acquired. The storage unit 18 stores a first reference model representing the shape of the object and a lookup table described later. The range adjustment unit 31 adjusts the installation possible range using the first reference model read from the storage unit 18. The exposure time adjustment unit 33 adjusts the exposure time using the lookup table read from the storage unit 18. Details of the configurations of each of the range adjustment unit 31, the measurement distance adjustment unit 32, and the exposure time adjustment unit 33 will be described later.

[0063] Next, a description will be given of the processing performed by the measurement condition setting unit 11. Fig. 9 is a flowchart showing the procedure of processing performed by the measurement condition setting unit 11 included in the measurement apparatus 10 according to the third embodiment.

[0064] In step S21, the range adjustment unit 31 of the measurement condition setting unit 11 adjusts the installation range of the object and the sensor 12. In step S22, the measurement distance adjustment unit 32 of the measurement condition setting unit 11 adjusts the measurement distance of the sensor 12. In step S23, the exposure time adjustment unit 33 of the measurement condition setting unit 11 adjusts the exposure time of the sensor 12. With the above, the measurement condition setting unit 11 ends the processing according to the procedure shown in Fig. 9. Details of the processing in each of the range adjustment unit 31, the measurement distance adjustment unit 32, and the exposure time adjustment unit 33 will be described later.

[0065] 10 is a diagram showing an example of the configuration of the range adjustment unit 31 included in the measurement condition setting unit 11 in the embodiment 3. The range adjustment unit 31 includes a scene generation unit , an interference determination unit 35, and a range determination unit .

[0066] The scene generating unit 34 generates a simulated scene when the object is captured by arranging the object, the sensor 12, and a structure around the object or the sensor 12 in a virtual space. The scene generating unit 34 acquires a first reference model from the storage unit 18. The scene generating unit 34 arranges the object indicated by the first reference model, the sensor 12, and the structure in the virtual space. For example, when the object is rotated by a rotating stage, the rotating stage and a driving unit of the rotating stage may be included in the structure around the object. The conditions for generating the simulated scene are manually set by the user of the measuring device 10. The scene generating unit 34 may automatically set the conditions based on default values ​​or preset values ​​prepared in advance.

[0067] The interference determination unit 35 determines whether or not there is interference between an object or the sensor 12 and a structure when at least one of the position of the object, the orientation of the object, the position of the sensor 12, and the orientation of the sensor 12 is changed in the scene.

[0068] The direction in which the position of the object is changed and the direction in which the position of the sensor 12 is changed can be set to any of the X-axis direction, the Y-axis direction, and the Z-axis direction. The rotation axis for changing the posture of the object and the rotation axis for changing the posture of the sensor 12 can be set to any of the A-axis, the B-axis, and the C-axis. The A-axis, the B-axis, and the C-axis are three rotation axes perpendicular to each other. The direction in which the position of the object is changed, the direction in which the position of the sensor 12 is changed, the rotation axis for changing the posture of the object, and the rotation axis for changing the posture of the sensor 12 are manually set by the user of the measuring device 10. The interference determination unit 35 may automatically set the direction in which the position of the object is changed, the direction in which the position of the sensor 12 is changed, the rotation axis for changing the posture of the object, and the rotation axis for changing the posture of the sensor 12 based on a default value or a preset value prepared in advance.

[0069] The range determination unit 36 ​​determines the installable range of the object and the sensor 12 based on the determination result by the interference determination unit 35. The range determination unit 36 ​​determines, for example, a range in which the object and the sensor 12 do not interfere with the object or structures around the sensor 12 as the installable range. In this manner, the measurement condition setting unit 11 sets the installable range, which is one of the measurement conditions, by determining the installable range in the range determination unit 36. With the object and the sensor 12 installed in the set installable range, the sensor 12 captures an image of the object, and the measurement unit 13 measures the object.

[0070] The position or orientation of the object or the position or orientation of the sensor 12 at the start of measurement by the measurement unit 13 is manually determined by the user based on the set possible installation range. Alternatively, the position or orientation of the object or the position or orientation of the sensor 12 at the start of measurement by the measurement unit 13 may be automatically determined by the measurement unit 13 based on the set possible installation range.

[0071] 11 is a diagram showing an example of the configuration of the measurement distance adjustment unit 32 included in the measurement condition setting unit 11 according to the embodiment 3. The measurement distance adjustment unit 32 includes a point cloud number acquisition unit 37 and a measurement distance determination unit .

[0072] The point cloud number acquisition unit 37 acquires a point cloud number, which is the number of points included in the three-dimensional point cloud data acquired by the sensor 12. For example, the point cloud number acquisition unit 37 acquires the point cloud number of the first reference model by simulating imaging of the first reference model in a virtual space. The point cloud number acquisition unit 37 acquires the point cloud number for each measurement distance by acquiring the point cloud number while changing the measurement distance within the installation possible range set by the range adjustment unit 31. The point cloud number acquisition unit 37 may acquire the point cloud number corresponding to the measurement distance and the observation angle by acquiring the point cloud number while changing the measurement distance and the observation angle of the sensor 12.

[0073] The measurement distance determination unit 38 determines the measurement distance at the time of imaging the object based on the point cloud number acquired for each measurement distance by the point cloud number acquisition unit 37. For example, the measurement distance determination unit 38 compares the point cloud numbers for each measurement distance and determines the measurement distance at which the point cloud number is maximum as the measurement distance at the time of imaging. When the point cloud number acquisition unit 37 acquires the point cloud number corresponding to the measurement distance and the observation angle, the measurement distance determination unit 38 may determine the measurement distance and the observation angle at the time of imaging based on the point cloud number acquired corresponding to the measurement distance and the observation angle.

[0074] In this manner, the measurement condition setting unit 11 sets the measurement distance, which is one of the measurement conditions, by determining the measurement distance in the measurement distance determination unit 38. The sensor 12 captures an image of the object at the set measurement distance, and the measurement unit 13 measures the object. Note that the method of setting the measurement distance is not limited to the method described in the third embodiment, and may be any method.

[0075] 12 is a diagram showing an example of the configuration of the exposure time adjustment unit 33 included in the measurement condition setting unit 11 in embodiment 3. The exposure time adjustment unit 33 includes a reflectance distribution acquisition unit 39, a data comparison unit 40, and an exposure time determination unit 41.

[0076] The reflectance distribution acquisition unit 39 acquires the reflectance distribution of the object. For example, the reflectance distribution acquisition unit 39 captures images of the object and a reflector whose reflectance is known under the same environment by the sensor 12, and obtains the reflectance distribution of the object based on the measurement result of the luminance value of the reflector. Note that the method of acquiring the reflectance distribution of the object is not limited to the method described in the third embodiment, and may be any method.

[0077] The lookup table stored in the storage unit 18 has a database that compiles reflectance distribution data for various objects. The lookup table includes reflectance distribution data for objects with relatively high glossiness and reflectance distribution data for objects with relatively low glossiness. The reflectance distribution data for various objects is acquired in advance based on the results of capturing images of the objects by the sensor 12, for example, and stored in the lookup table.

[0078] The data comparison unit 40 compares the reflectance distribution of the object with the reflectance distribution data stored in advance in a lookup table. The data comparison unit 40 determines the degree of similarity between the reflectance distribution data stored in the lookup table and the reflectance distribution of the object through such comparison.

[0079] The data comparison unit 40 obtains the degree of similarity between the reflectance distribution of the object and the reflectance distribution stored in advance in the lookup table, for example, using the following formula (3). g(M) represents the reflectance distribution data of the object. g(P) represents the reflectance distribution data of an object stored in advance in the lookup table. The smaller the value shown in formula (3), the higher the similarity between the reflectance distribution of the object and the reflectance distribution of object g(P).

[0080]

number

[0081] In the lookup table, reflectance distribution data for each object is associated with parameter values ​​related to measurement using the sensor 12. The parameters related to the measurement are, for example, exposure time or gain. The reflectance distribution data for each object is associated with parameter values ​​suitable for measuring the object by the sensor 12. The parameter values ​​suitable for measurement are determined in advance based on, for example, the results of capturing an image of the object by the sensor 12.

[0082] The exposure time determination unit 41 determines the exposure time of the sensor 12 based on the comparison result by the data comparison unit 40. The exposure time determination unit 41 selects the reflectance distribution data having the highest similarity to the reflectance distribution of the object from among the reflectance distribution data stored in the lookup table. The exposure time determination unit 41 determines the exposure time associated with the selected reflectance distribution data as the exposure time at the time of imaging. Note that the values ​​of parameters other than the exposure time among the parameters related to the measurement may be determined in the same manner as the exposure time. The exposure time determination unit 41 may determine the gain associated with the selected reflectance distribution data as the gain at the time of imaging.

[0083] In this manner, the measurement condition setting unit 11 sets the exposure time, which is one of the measurement conditions, by determining the exposure time in the exposure time determination unit 41. The sensor 12 captures an image of the object at the set exposure time, and the measurement unit 13 measures the object. Note that the method of setting the exposure time is not limited to the method described in the third embodiment, and may be any method.

[0084] Next, a description will be given of the processing by the range adjustment unit 31, the measurement distance adjustment unit 32, and the exposure time adjustment unit 33. Fig. 13 is a flowchart showing the procedure of the processing by the range adjustment unit 31, the measurement distance adjustment unit 32, and the exposure time adjustment unit 33 included in the measurement device 10 according to the third embodiment.

[0085] In step S31, the scene generation unit 34 of the range adjustment unit 31 simulates a scene when the object is imaged. In step S32, the interference determination unit 35 of the range adjustment unit 31 determines whether or not there is interference between the object or the sensor 12 and a structure in the scene generated in step S31. In step S33, the range determination unit 36 ​​of the range adjustment unit 31 determines the possible installation range of the object and the sensor 12 based on the determination result in step S32.

[0086] In step S34, the point cloud number acquisition unit 37 of the measurement distance adjustment unit 32 acquires the number of point clouds. In step S35, the measurement distance determination unit 38 of the measurement distance adjustment unit 32 determines the measurement distance when the object is imaged, based on the number of point clouds acquired in step S34.

[0087] In step S36, the reflectance distribution acquisition unit 39 of the exposure time adjustment unit 33 acquires the reflectance distribution of the object. In step S37, the data comparison unit 40 of the exposure time adjustment unit 33 compares the reflectance distribution of the object acquired in step S36 with the data in the lookup table. In step S38, the exposure time determination unit 41 of the exposure time adjustment unit 33 determines the exposure time when capturing an image of the object based on the comparison result in step S37. With the above, the range adjustment unit 31, the measurement distance adjustment unit 32, and the exposure time adjustment unit 33 end the processing according to the procedure shown in FIG.

[0088] According to the third embodiment, the measurement condition setting unit 11 sets the possible installation range, the measurement distance, and the exposure time when the image information is acquired. The measurement device 10 can set measurement conditions suitable for the measurement of the object by the measurement unit 13. As described above, the measurement device 10 has an effect of being able to accurately identify a processing area where material is to be added or cut for an object to which material is to be added or cut.

[0089] Embodiment 4 In the fourth embodiment, a configuration example of the machining area specifying unit 17 will be described. Fig. 14 is a diagram showing a configuration example of the machining area specifying unit 17 included in the measuring device 10 according to the fourth embodiment. The machining area specifying unit 17 includes a noise removing unit 51, a position adjusting unit 52, and a machining area determining unit 53.

[0090] The noise removal unit 51 removes noise from the measurement data complemented by the measurement data complementation unit 16. For example, the noise removal unit 51 sets a threshold value for each coordinate of the three-dimensional point cloud data, which is the measurement data, and regards data outside the range defined by the threshold value as noise and removes the noise.

[0091] When the object has a simple shape such as a rectangular parallelepiped, the noise removal unit 51 may estimate a primitive shape, which is a combination of planes, and remove data that deviates from the estimated primitive shape, regarding it as noise. The noise removal unit 51 may remove data that deviates from the primitive shape from among the measurement data by using a RANSAC (RANdom SAmple Consensus) method. The noise removal unit 51 may perform statistical processing of the three-dimensional point cloud data, and remove noise based on the statistical values. Note that the method of removing noise is not limited to the method described in the fourth embodiment, and may be any method.

[0092] The alignment unit 52 aligns the measurement data from which noise has been removed by the noise removal unit 51 with a second reference model, which is a model of a finished product obtained by adding or cutting. The alignment unit 52 performs alignment using ICP (Iterative Closest Point) or alignment based on feature points.

[0093] The alignment unit 52 may align the measurement data to the entire second reference model by ICP or the like, and may also designate a part of the second reference model and perform alignment using the designated part as a reference. For example, when the target object has a complex or special shape, or when the target object is a molded product that is larger in size than the finished product, the alignment unit 52 may perform alignment using a special part of the target object, such as a part where a notch is provided, as a reference. The result of the alignment by the alignment unit 52 may be manually fine-tuned by the user. The alignment method is not limited to the method described in the fourth embodiment, and may be any method.

[0094] The machining area determination unit 53 determines a machining area, which is an addition area or a cutting area, based on the measurement data and the second reference model that have been aligned by the alignment unit 52. The machining area determination unit 53 determines the machining area by calculating a difference between the measurement data and the second reference model.

[0095] When determining the additional area, the processing area determination unit 53 determines the difference obtained by subtracting the three-dimensional point cloud data from the second reference model, that is, the area that exists in the second reference model but does not exist in the three-dimensional point cloud data, as the additional area. For example, the processing area determination unit 53 calculates the difference between the vertices in the second reference model and the three-dimensional point cloud data, and outputs the calculation result of the difference at the vertices as data indicating the determined additional area. The processing area determination unit 53 may output two types of data, the calculation result of the difference at the vertices and the mesh, as data indicating the determined additional area. If the second reference model has few vertices and it is difficult to express the additional area by the calculation result of the difference at the vertices, the processing area determination unit 53 may convert the second reference model into three-dimensional point cloud data, and then calculate the difference between the three-dimensional point cloud data that is the second reference model and the three-dimensional point cloud data that is the measurement data. In this way, the processing area specification unit 17 specifies the additional area by determining the additional area using the processing area determination unit 53. The method for determining the additional region is not limited to the method described in the fourth embodiment, but may be any method.

[0096] When determining the cutting area, the machining area determination unit 53 determines the difference obtained by subtracting the second reference model from the three-dimensional point cloud data, that is, the area that exists in the three-dimensional point cloud data but does not exist in the second reference model, as the cutting area. The machining area determination unit 53, for example, calculates the difference between the three-dimensional point cloud data and the vertices in the second reference model, and outputs the calculation result of the difference at the vertices as data indicating the determined cutting area. The machining area determination unit 53 may output two types of data, the calculation result of the difference at the vertices and the mesh, as data indicating the determined cutting area. If the second reference model has few vertices and it is difficult to express the cutting area by the calculation result of the difference at the vertices, the machining area determination unit 53 may convert the second reference model into three-dimensional point cloud data, and then calculate the difference between the three-dimensional point cloud data that is the measurement data and the three-dimensional point cloud data that is the second reference model. In this way, the machining area specification unit 17 specifies the cutting area by determining the cutting area using the machining area determination unit 53. The method for determining the cutting area is not limited to the method described in the fourth embodiment, but may be any method.

[0097] Next, a process performed by the processing area specifying unit 17 will be described. Fig. 15 is a first flowchart showing a procedure of a process performed by the processing area specifying unit 17 included in the measuring device 10 according to the fourth embodiment. Fig. 15 shows a procedure of a process performed when the processing area specifying unit 17 specifies an additional area.

[0098] In step S41, the noise removal unit 51 of the machining area specifying unit 17 removes noise from the measurement data complemented by the measurement data complementing unit 16. In step S42, the alignment unit 52 of the machining area specifying unit 17 aligns the measurement data from which noise has been removed in step S41 with a second reference model, which is a model of a completed product by addition.

[0099] In step S43, the processing area determination unit 53 of the processing area specifying unit 17 determines the additional area based on the measurement data and the second reference model aligned in step S42. With the above, the processing area specifying unit 17 ends the process according to the procedure shown in FIG.

[0100] Fig. 16 is a second flowchart showing the procedure of the process by the machining area specifying unit 17 included in the measuring device 10 according to the embodiment 4. Fig. 16 shows the procedure of the process when the machining area specifying unit 17 specifies the cutting area.

[0101] The procedures of steps S41 and S42 shown in Fig. 16 are similar to the procedures of steps S41 and S42 shown in Fig. 15. After completing step S42 shown in Fig. 16, the processing region specifying unit 17 advances the procedure to step S44.

[0102] In step S44, the machining area determination unit 53 of the machining area specifying unit 17 determines the cutting area based on the measurement data aligned in step S42 and the second reference model. With the above, the machining area specifying unit 17 ends the processing according to the procedure shown in FIG.

[0103] According to the fourth embodiment, the machining area specifying unit 17 removes noise from the measurement data, and then aligns the measurement data with the second reference model to determine the machining area. The measuring device 10 can accurately specify the machining area by the machining area specifying unit 17. As described above, the measuring device 10 has an effect of being able to accurately specify the machining area to which material is to be added or cut for the object to which material is to be added or cut.

[0104] Embodiment 5. In the fifth embodiment, an additional processing system having a measuring device 10 will be described. Fig. 17 is a diagram showing a configuration example of an additional processing system 60 according to the fifth embodiment. The additional processing system 60 has the measuring device 10, a mesh generating device 61, a computer aided manufacturing (CAM) device 62, and an additional processing device 63.

[0105] The measuring device 10 measures the shape of the object to identify an addition region to be added. The measuring device 10 of the additive machining system 60 may be any of the measuring devices 10 according to the first to fourth embodiments. The mesh generating device 61 generates a mesh model. The CAM device 62 generates a machining path for adding material to the object and generates a machining program. The additive machining device 63 is a machine tool that manufactures a shaped object by adding material to the object.

[0106] The mesh generating device 61 is a computer system in which a program for generating a mesh model is installed. The CAM device 62 is a computer system in which CAM software is installed. The CAM software is a program for generating a machining path and a machining program. The functions of the mesh generating device 61 and the CAM device 62 are realized by using a processing circuit 80 having a processor 82 and a memory 83, similar to the case of the hardware configuration shown in FIG. 2.

[0107] The mesh generating device 61 generates a mesh model of the additional area specified by the machining area specifying unit 17 shown in Fig. 1. The mesh generating device 61, for example, acquires three-dimensional point cloud data representing the additional area, and generates a mesh model from the three-dimensional point cloud data. The mesh generating device 61 may receive the result of the specification by the machining area specifying unit 17 as part of the mesh data of the second reference model, which is a model of the finished product, and generate a mesh model only for the area where some mesh is missing.

[0108] The CAM device 62 determines a machining path based on the mesh model generated by the mesh generating device 61, and generates a machining program by converting the machining path into a machining program. The additional processing device 63 manufactures a molded object in accordance with the machining program generated by the CAM device 62.

[0109] The additive processing device 63 manufactures a shaped object by adding a material melted by irradiation of a beam to an object. The beam, which is a heat source, is a laser beam or an electron beam, or the like. Instead of a beam, an arc may be used as a heat source. The additive processing device 63 may be equipped with peripheral devices, such as a device for monitoring the shaped object during production, or a device for measuring the temperature or oxygen concentration inside the additive processing device 63. FIG. 17 shows an additive processing system 60 equipped with one additive processing device 63. The additive processing system 60 shown in FIG. 17 manufactures a shaped object using one additive processing device 63. The additive processing system 60 may be equipped with multiple additive processing devices 63, and may manufacture a shaped object using multiple additive processing devices 63.

[0110] Next, the operation of the additional processing system 60 will be described. Fig. 18 is a flowchart showing the operation procedure of the additional processing system 60 according to the fifth embodiment. In step S51, the measuring device 10 of the additional processing system 60 measures the shape of the target object to identify the additional area. The measuring device 10 identifies the additional area by a procedure similar to that shown in Fig. 3.

[0111] In step S52, the mesh generating device 61 of the additive processing system 60 generates a mesh model of the additional area identified in step S51. In step S53, the CAM device 62 of the additive processing system 60 generates a processing path and a processing program based on the mesh model generated in step S52. In step S54, the additive processing device 63 of the additive processing system 60 manufactures a shaped object by adding material to the target object. With the above, the additive processing system 60 ends the operation according to the procedure shown in FIG.

[0112] According to the fifth embodiment, the additive processing system 60 is equipped with the measuring device 10, and thus can accurately identify the additional area. The additive processing system 60 can manufacture a highly accurate molded object by accurately identifying the additional area. Furthermore, the additive processing system 60 can improve the efficiency of the setup work up to the manufacture of the molded object by consistently performing the process from the measurement of the target object to the manufacture of the molded object. The additive processing system 60 can shorten the time required for the setup work and reduce the cost required for the setup work. The additive processing system 60 can reduce the time and cost required from the introduction of the additive processing device 63 to the verification of the manufacture of the molded object.

[0113] Embodiment 6 In the sixth embodiment, a cutting system having a measuring device 10 will be described. Fig. 19 is a diagram showing a configuration example of a cutting system 70 according to the sixth embodiment. The cutting system 70 has the measuring device 10, a mesh generating device 71, a CAM device 72, a cutting device 73, and an additional processing device 74.

[0114] The measuring device 10 measures the shape of the object to identify a cutting region where cutting is to be performed. The measuring device 10 of the cutting processing system 70 may be any of the measuring devices 10 according to the first to fourth embodiments. In the sixth embodiment, the object is a shaped object manufactured by an additive processing device 74.

[0115] The mesh generating device 71 generates a mesh model. The CAM device 72 generates a machining path for cutting an object and generates a machining program. The cutting device 73 is a machine tool that manufactures a processed product by cutting.

[0116] The mesh generating device 71 is a computer system in which a program for generating a mesh model is installed. The CAM device 72 is a computer system in which CAM software is installed. The CAM software is a program for generating a machining path and a machining program. The functions of the mesh generating device 71 and the CAM device 72 are realized by using a processing circuit 80 having a processor 82 and a memory 83, similar to the case of the hardware configuration shown in FIG. 2.

[0117] The mesh generating device 71 generates a mesh model of the cutting area identified by the machining area identifying unit 17 shown in Fig. 1. The mesh generating device 71 may generate the mesh model from the measurement data aligned with the second reference model by the machining area identifying unit 17.

[0118] The CAM device 72 obtains a machining path based on the mesh model generated by the mesh generating device 71, and generates the machining program by converting the machining path into a machining program. The CAM device 72 may use data indicating the difference between the result of identification by the machining area identifying unit 17 and a second reference model, which is a model of the finished product, to generate the machining path and the machining program. The cutting device 73 performs cutting according to the machining program generated by the CAM device 72.

[0119] The additive processing device 74 manufactures a shaped object by adding material that has been melted by irradiation with a beam. The shaped object manufactured by the additive processing device 74 is transported to the cutting device 73.

[0120] The cutting device 73 manufactures a processed product by cutting a shaped object, which is a target object. The cutting device 73 may be equipped with peripheral devices, such as devices for monitoring the processed product during cutting. FIG. 19 shows a cutting system 70 including one cutting device 73. The cutting system 70 shown in FIG. 19 manufactures a processed product by cutting with one cutting device 73. The cutting system 70 may include a plurality of cutting devices 73, and may manufacture a processed product by cutting with the plurality of cutting devices 73.

[0121] Next, the operation of the cutting system 70 will be described. Fig. 20 is a flowchart showing the operation procedure of the cutting system 70 according to the sixth embodiment. In step S61, the measuring device 10 of the cutting system 70 measures the shape of the target object to identify the cutting area. The target object is a shaped object manufactured by the additive processing device 74. The measuring device 10 identifies the cutting area by a procedure similar to that shown in Fig. 4.

[0122] In step S62, the mesh generating device 71 of the cutting system 70 generates a mesh model of the cutting area identified in step S61. In step S63, the CAM device 72 of the cutting system 70 generates a machining path and a machining program based on the mesh model generated in step S62.

[0123] In step S64, the cutting device 73 of the cutting system 70 cuts the object to manufacture a processed product. With the above, the cutting system 70 ends the operation according to the procedure shown in FIG.

[0124] According to the sixth embodiment, the cutting system 70 is provided with the measuring device 10, and thus can accurately identify the cutting area. The cutting system 70 can manufacture processed products with high accuracy by accurately identifying the cutting area. Furthermore, the cutting system 70 can improve the efficiency of the setup work up to the manufacture of the processed product by consistently performing the process from the measurement of the target object to the manufacture of the processed product. The cutting system 70 can shorten the time required for the setup work and can reduce the cost required for the setup work. The cutting system 70 can reduce the time and cost required from the introduction of the cutting device 73 to the verification of the manufacture of the processed product.

[0125] In the cutting system 70, the object on which the cutting device 73 performs cutting is not limited to a shaped object manufactured by the additive processing device 74. In the cutting system 70, the cutting device 73 may manufacture a processed product by cutting an object other than a shaped object manufactured by the additive processing device 74. The cutting system 70 may include at least the measuring device 10 and the cutting device 73. The cutting system 70 may not include the additional processing device 74.

[0126] Embodiment 7 The mesh generating devices 61 and 71 of the fifth and sixth embodiments may generate mesh models using a learning algorithm such as a neural network. In the seventh embodiment, the mesh generating devices 61 and 71 that generate mesh models using a neural network will be described.

[0127] The neural network receives data indicating the additional area or the cutting area, which is the result of identification by the machining area identification unit 17 shown in FIG. 1. The neural network outputs a mesh model in a preset representation method for the input data, which is data indicating the additional area or data indicating the cutting area. When data indicating the additional area is input, the input data may be three-dimensional point cloud data representing the additional area. When data indicating the cutting area is input, the input data may be measurement data aligned with a second reference model. As the neural network, for example, a GAN (Generative Adversarial Network) can be used.

[0128] The mesh generators 61 and 71 can generate meshes using the high expressive power of neural networks. Neural networks are expected to be more versatile than manually constructed mesh generation algorithms. This allows the mesh generators 61 and 71 to generate mesh models for objects of various shapes or sizes.

[0129] The input data, which is the learning data input to the mesh generating devices 61 and 71, and the network configuration of the mesh generating devices 61 and 71 are not limited to those described in the seventh embodiment. The learning data may be any data. Furthermore, any network configuration may be used for the mesh generating devices 61 and 71.

[0130] The configurations shown in the above embodiments are examples of the contents of the present disclosure. The configurations of each embodiment can be combined with other known technologies. The configurations of each embodiment can be appropriately combined. A part of the configuration of each embodiment can be omitted or modified without departing from the gist of the present disclosure. [Explanation of symbols]

[0131] 10 Measurement device, 11 Measurement condition setting unit, 12 Sensor, 13 Measurement unit, 14 Measurement data integration unit, 15 Defect area detection unit, 16 Measurement data complementation unit, 17 Processing area identification unit, 18 Memory unit, 21 Defect candidate point detection unit, 22 Contour extraction unit, 23 Area calculation unit, 24 Defect determination unit, 25 Normal distribution calculation unit, 26 Position and orientation calculation unit, 27 Remeasurement unit, 28 Reintegration unit, 31 Range adjustment unit, 32 Measurement distance adjustment unit, 33 Exposure time adjustment unit, 34 Scene generation unit, 35 Interference determination unit, 36 Range determination unit, 37 Point cloud number acquisition unit, 38 Measurement distance determination unit, 39 Reflectance distribution acquisition unit, 40 Data comparison unit, 41 Exposure time determination unit, 51 Noise removal unit, 52 Alignment unit, 53 Processing area determination unit, 60 Additional processing system, 61, 71 Mesh generating device, 62, 72 CAM device, 63, 74 Additional processing device, 70 Cutting system, 73 Cutting device, 80 Processing circuit, 81 Input unit, 82 Processor, 83 Memory, 84 Output unit.

Claims

1. a sensor for acquiring image information by imaging an object to which material is to be added or removed; a measurement unit that measures a shape of the object based on the image information to obtain measurement data indicating the shape of the object; a missing area detection unit that detects a missing area of ​​the object, the missing area being an area where the measurement data is missing; a measurement data complementation unit that acquires remeasurement data, which is measurement data for the missing area, by re-measuring the shape of the object based on the image information acquired by re-imaging the sensor, and complements the measurement data with the remeasurement data; a processing area specifying unit that specifies a processing area to be added or cut based on a model of a finished product obtained by the addition or cut and the supplemented measurement data; Equipped with The defective area detection unit a loss candidate point detection unit that detects loss candidate points that are candidates for points included in a contour of the loss area from the measurement data acquired by the measurement unit; a contour extraction unit that extracts a contour including the loss candidate point from the data of the loss candidate point; an area calculation unit that calculates an area of ​​a region surrounded by the contour; a loss determination unit that determines whether or not a region surrounded by the contour is a loss region based on the calculated area; A measuring device comprising:

2. The measurement data complementation unit a normal distribution calculation unit that calculates a normal distribution, which is a distribution of directions of normals in the missing area detected by the missing area detection unit; a position and orientation calculation unit that calculates a position or orientation of the object or a position or orientation of the sensor based on the normal distribution such that the sensor faces the object; a remeasurement unit that acquires the remeasurement data by re-measuring a shape of the object based on the image information acquired by re-imaging the sensor after the position or orientation of the object or the position or orientation of the sensor is corrected; a reintegration unit that integrates the remeasurement data with the measurement data; The measuring device according to claim 1 , further comprising:

3. a measurement condition setting unit that sets measurement conditions for the measurement by the measurement unit, The measurement condition setting unit is a range adjustment unit that adjusts a range in which the object and the sensor can be placed when the image information is acquired; a measurement distance adjustment unit that adjusts the measurement distance of the sensor; an exposure time adjustment unit that adjusts an exposure time of the sensor; 3. The measuring device according to claim 1, further comprising:

4. The range adjustment unit is a scene generation unit that generates a simulation of a scene when the object is captured by arranging the object, the sensor, and a structure around the object or the sensor in a virtual space; an interference determination unit that determines whether or not there is interference between the object or the sensor and the structure when at least one of a position of the object, an attitude of the object, a position of the sensor, and an attitude of the sensor is changed in the scene; a range determination unit that determines the range in which the object and the sensor can be installed based on a determination result by the interference determination unit; 4. The measuring device according to claim 3, further comprising:

5. The measurement distance adjustment unit is a point cloud number acquisition unit that acquires a point cloud number, which is the number of points included in the three-dimensional point cloud data acquired by the sensor, for each measurement distance, which is the distance from the object to the sensor; a measurement distance determination unit that determines a measurement distance at the time of capturing an image of the object based on the number of points acquired for each measurement distance; 5. The measuring device according to claim 3, further comprising:

6. The exposure time adjustment unit is a reflectance distribution acquisition unit that acquires a reflectance distribution of the object; a data comparison unit that compares the reflectance distribution with previously stored reflectance distribution data; an exposure time determination unit that determines the exposure time based on a comparison result by the data comparison unit; 6. The measuring device according to claim 3, further comprising:

7. The processing area specifying unit is a noise removal unit that removes noise from the measurement data complemented by the measurement data complementing unit; a registration unit that performs registration between the measurement data from which the noise has been removed and the model; a machining area determination unit that determines the machining area based on the measurement data and the model that have been aligned; 7. The measuring device according to claim 1, further comprising:

8. an additive processing device for manufacturing a structure by adding material to an object; a measuring device that measures a shape of the object to identify an addition area to be added; a mesh generating device for generating a mesh model of the additional region; a computer-aided manufacturing device that generates a processing program based on the mesh model; Equipped with The measuring device includes: a sensor for acquiring image information by capturing an image of the object; a measurement unit that measures a shape of the object based on the image information to obtain measurement data indicating the shape of the object; a missing area detection unit that detects a missing area of ​​the object, the missing area being an area where the measurement data is missing; a measurement data complementation unit that acquires remeasurement data, which is measurement data for the missing area, by re-measuring the shape of the object based on the image information acquired by re-imaging the sensor, and complements the measurement data with the remeasurement data; a processing area specifying unit that specifies the additional area based on a model showing a shape after processing and the interpolated measurement data; having The mesh generating device generates the mesh model of the additional area specified by the processing area specifying unit, The additive processing system is characterized in that the additive processing device manufactures the object in accordance with the processing program.

9. The additional processing system according to claim 8, characterized in that the mesh generating device generates the mesh model using a neural network that outputs the mesh model in response to input data indicating the additional area identified by the processing area identification unit.

10. A cutting processing device for manufacturing a processed product by cutting an object; a measuring device that measures a shape of the object to specify a cutting area in which the cutting is to be performed; a mesh generating device for generating a mesh model of the cutting area; a computer-aided manufacturing device that generates a processing program based on the mesh model; Equipped with The measuring device includes: a sensor for acquiring image information by capturing an image of the object; a measurement unit that measures a shape of the object based on the image information to obtain measurement data indicating the shape of the object; a missing area detection unit that detects a missing area of ​​the object, the missing area being an area where the measurement data is missing; a measurement data complementation unit that acquires remeasurement data, which is measurement data for the missing area, by re-measuring the shape of the object based on the image information acquired by re-imaging the sensor, and complements the measurement data with the remeasurement data; a machining area specifying unit that specifies the cutting area based on a model showing a shape after machining and the interpolated measurement data; having The mesh generating device generates the mesh model of the cutting area identified by the machining area identifying unit, The cutting system is characterized in that the cutting device manufactures the processed product in accordance with the processing program.

11. The cutting processing system according to claim 10, characterized in that the mesh generating device generates the mesh model using a neural network that outputs the mesh model in response to input data indicating the cutting area identified by the machining area identification unit.

12. and further comprising an additive processing device for producing a shaped article by the addition of material; the measuring device measures a shape of the shaped product, which is the target object, to identify a cutting area in which the cutting is to be performed; The cutting system according to claim 10 or 11, wherein the cutting device manufactures the processed product by cutting the shaped product.

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