Measuring device, additional processing system and cutting processing system

Abstract

A measurement device (10) has a sensor (12) that acquires image information by taking a picture of an object on which addition or cutting of a material is performed, a measurement unit (13) that measures a shape of the object based on the image information, thereby acquiring measurement data that represents the shape of the object, a missing region detection unit (15) that detects a region in the object in which the measurement data is missing, i.e., a missing region, a measurement data complementing unit (16) that re-measures the shape of the object based on image information acquired by a re-picture taken by the sensor (12), thereby acquiring re-measurement data that is measurement data related to the missing region, and that complements the measurement data with the re-measurement data, and a processing region determination unit (17) that determines a processing region on which the addition or cutting is performed based on a model of a finished product resulting from the addition or cutting and the complemented measurement data.

Description

Technical Field

[0001] This invention relates to a measuring device, an additional machining system, and a cutting machining system for measuring objects that are applied to or cut by a material. Background Technology

[0002] In the case of machining performed by attaching material to an object or by cutting the object, the shape of the object is measured, thereby determining the machining area within the object where the attachment or cutting is performed. To determine the machining area, 3D measurement data of the object is required.

[0003] Patent Document 1 discloses a machining apparatus for machining a cutting tool by removing material. Specifically, in the case of re-machining a damaged cutting tool that has been used and is now in use, the measuring unit of the machining apparatus uses a sensor to perform 3D measurement of the tool's profile, obtaining 3D measurement data of the tool. Based on the difference between the tool model formed from the 3D measurement data and a pre-set reference profile, the measuring unit determines the machining area within the tool where material is removed.

[0004] Patent Document 1: Japanese Patent Publication No. 2018-516178 Summary of the Invention

[0005] In measurements used to determine the processing area, measurement omissions sometimes occur due to blind spots when detecting the shape or size of the object. If measurement omissions occur, it becomes difficult to accurately determine the processing area. The technology in Patent Document 1 does not consider measurement omissions caused by blind spots, thus making it difficult to accurately determine the processing area depending on the object.

[0006] The present invention was made in view of the above circumstances, and its object is to provide a measuring device that can accurately determine the processing area for adding or cutting materials.

[0007] To address the aforementioned issues and achieve the objectives, the measuring apparatus of the present invention comprises: a sensor that acquires image information by photographing an object on which material is added or cut; a measuring unit that measures the shape of the object based on the image information, thereby acquiring measurement data representing the shape of the object; a defect area detection unit that detects areas in the object where measurement data is missing, i.e., defect areas; a measurement data completion unit that remeasures the shape of the object based on image information acquired by re-photographing through the sensor, thereby acquiring measurement data related to the defect areas, i.e., remeasurement data, and completes the measurement data using the remeasurement data; and a processing area determination unit that determines the processing area on which the addition or cutting is performed based on a model of the finished product obtained by addition or cutting and the completed measurement data.

[0008] The effects of the invention

[0009] The measuring device involved in this invention has the following effect: it can accurately determine the processing area where the material is added or cut, with respect to the object to which the material is added or cut. Attached Figure Description

[0010] Figure 1 This is a diagram showing the functional structure of the measuring device involved in Embodiment 1.

[0011] Figure 2 This is a diagram showing an example of the hardware structure of the processing unit used to implement the measuring device according to Embodiment 1.

[0012] Figure 3 This is a first flowchart showing the sequence of processes performed by the measuring device according to Embodiment 1.

[0013] Figure 4 This is a second flowchart showing the sequence of processes performed by the measuring device according to Embodiment 1.

[0014] Figure 5 This is a diagram illustrating a structural example of the defect detection unit in the measuring device according to Embodiment 2.

[0015] Figure 6 This is a diagram illustrating a structural example of the complete measurement data supplement of the measuring device according to Embodiment 2.

[0016] Figure 7 This is a flowchart illustrating the sequence of processing performed by the defect detection unit and measurement data supplementation unit of the measuring device according to Embodiment 2.

[0017] Figure 8This is a diagram illustrating a structural example of the measurement condition setting unit of the measuring device according to Embodiment 3.

[0018] Figure 9 This is a flowchart showing the sequence of processes performed by the measurement condition setting unit of the measuring device according to Embodiment 3.

[0019] Figure 10 This is a diagram illustrating a structural example of the range adjustment unit included in the measurement condition setting unit of Embodiment 3.

[0020] Figure 11 This is a diagram showing an example of the structure of the measurement distance adjustment unit in the measurement condition setting unit of Embodiment 3.

[0021] Figure 12 This is a diagram illustrating a structural example of the exposure time adjustment unit included in the measurement condition setting unit of Embodiment 3.

[0022] Figure 13 This is a flowchart showing the sequence of processes performed by the range adjustment unit, measurement distance adjustment unit, and exposure time adjustment unit of the measuring device according to Embodiment 3.

[0023] Figure 14 This is a diagram illustrating a structural example of the processing area determination section of the measuring device according to Embodiment 4.

[0024] Figure 15 This is a first flowchart showing the sequence of processes performed by the processing area determination unit of the measuring device according to Embodiment 4.

[0025] Figure 16 This is a second flowchart showing the sequence of processes performed by the processing area determination unit of the measuring device according to Embodiment 4.

[0026] Figure 17 This is a diagram illustrating a structural example of the additional processing system involved in Embodiment 5.

[0027] Figure 18 This is a flowchart illustrating the sequence of operations of the additional processing system involved in Implementation 5.

[0028] Figure 19 This is a diagram illustrating a structural example of the cutting system involved in Embodiment 6.

[0029] Figure 20 This is a flowchart illustrating the sequence of operations of the cutting system involved in Embodiment 6. Detailed Implementation

[0030] The measuring device, additional machining system, and cutting machining system involved in the embodiments will now be described in detail based on the accompanying drawings.

[0031] Implementation method 1.

[0032] Figure 1 This is a diagram illustrating the functional structure of the measuring device 10 according to Embodiment 1. The measuring device 10 measures the shape of the object to which the material is applied or cut, thereby determining the processing area in the object. The processing area is the area in the object to which the material is applied or cut. In the following description, the processing area to which the material is applied will be referred to as the application area, and the processing area to which the material is cut will be referred to as the cutting area.

[0033] The measuring device 10 includes: a measurement condition setting unit 11 for setting measurement conditions; a sensor 12 for taking pictures of the object; a measuring unit 13 for measuring the shape of the object; and a storage unit 18 for storing various information. Additionally, the measuring device 10 includes a measurement data merging unit 14, a defect area detection unit 15, a measurement data completion unit 16, and a processing area determination unit 17.

[0034] Sensor 12 acquires image information by photographing the object. Sensor 12 is a 2D camera or a 3D sensor. The image information acquired by sensor 12 is 2D data such as grayscale or color images, or 3D data such as 3D point group data or distance images. Sensor 12 can be, for example, two 2D laser scanners. 3D data can be acquired by alternately arranging the two 2D laser scanners in a crosshair configuration. Alternately arranging the two 2D laser scanners in a crosshair configuration means that the scanning planes of one 2D laser scanner and the scanning planes of the other 2D laser scanner are arranged in a manner that are orthogonal to each other. In the following description, it is assumed that the measuring device 10 acquires 3D data to measure the object.

[0035] The measurement condition setting unit 11 sets the measurement conditions for performing the measurement executed by the measurement unit 13. The measurement conditions include a settable range, measurement distance, observation angle, and exposure time. The settable range is the range within which the object and sensor 12 can be set when acquiring image information. The measurement distance is the distance from the object to the sensor 12. The observation angle is the angle representing the direction of the sensor 12 relative to the object. The exposure time is the exposure time of the sensor 12 during image capture. The measurement condition setting unit 11 sets the measurement conditions in accordance with the state of the object. Furthermore, the measurement conditions are not limited to those described in Embodiment 1. Any measurement condition can be any condition required for the measurement.

[0036] 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 through simulation. When setting the measurement conditions through simulation, the measurement condition setting unit 11 configures the sensor 12 and the object in an imaginary space, simulates the scene when the object is photographed by the sensor 12, and thereby sets the measurement conditions. The measurement condition setting unit 11 reads a first reference model representing the shape of the object from the storage unit 18 and configures the first reference model in the imaginary space. The first reference model is pre-stored in the storage unit 18.

[0037] The measuring unit 13 measures the shape of the object based on image information, thereby obtaining measurement data representing the shape of the object. The measurement data is 2D data or 3D data. The object is, for example, positioned on a rotary table that can rotate about axis A and about axis B. A and B are set as two rotation axes that are perpendicular to each other.

[0038] The measuring unit 13 uses a rotary table to rotate the object, thereby changing the object's posture. While changing the object's posture, the measuring unit 13 uses the sensor 12 to photograph the object, thereby measuring the object's shape. When the rotary table is controlled in coordination with the sensor 12 by a controller such as a CNC device, the measuring unit 13 automatically measures the object.

[0039] The measuring unit 13 measures the shape of the object by changing its relative position or orientation relative to the sensor 12. Specifically, the measuring unit 13 measures the object by changing at least one of the object's position, its orientation, the sensor 12's position, and its orientation. The directions of position change for both the object and the sensor 12 can be any of the X-axis, Y-axis, and Z-axis. The X-axis, Y-axis, and Z-axis are set to be three mutually perpendicular axes.

[0040] The object can be grasped by the robot arm and rotated by the arm's movement. Alternatively, the sensor 12 can be mounted on the robot arm, and the position or orientation of the sensor 12 can be changed by the arm's movement. The device that changes at least one of the position, orientation of the object, position, and orientation of the sensor 12 is not limited to a rotary table or a robot, but can be other devices.

[0041] The measurement data merging unit 14 merges measurement data acquired by the measurement unit 13 at different times. For example, the measurement data merging unit 14 calculates the center position of the rotary table and merges measurement data based on that center position. If the measurement data acquired by the measurement unit 13 contains unwanted data, such as data related to the background of the object, the measurement data merging unit 14 can use a background subtraction method to remove the unwanted background data. Therefore, the measurement data merging unit 14 can merge only the measurement data related to the object.

[0042] The defect area detection unit 15 detects defect areas based on the measurement data merged by the measurement data merging unit 14. A defect area is a region within an object where measurement data is missing. Depending on the shape or size of the object, measurement omissions sometimes occur due to blind spots of the sensor 12. Measurement data is lost due to these omissions.

[0043] For example, the defect detection unit 15 extracts the outline of the object from the 3D point group data used as measurement data, compares the extracted outline with the outline of the second reference model, and thereby detects the defect area. The second reference model is a model of the finished product obtained by attachment or cutting. The second reference model is preset in the measuring device 10. The defect detection unit 15 can perform statistical processing of the 3D point group data and detect the defect area based on the statistical values.

[0044] The measurement data completion 16 remeasures the shape of the object based on the image information obtained by re-capturing through the sensor 12, thereby obtaining measurement data related to the defect area, i.e., remeasurement data, and completes the measurement data using the remeasurement data. When the location of the defect area or the object's posture when the defect area is directly opposite the sensor 12 is known through the defect area detection unit 15, the measurement data completion 16 can remeasure by changing the object's position or posture to match the known position or posture. The measurement data completion 16 can also remeasure by adding changes to the object's position or posture compared to measurements performed through the measurement unit 13. Similarly, the measurement data completion 16 can remeasure by adding changes to the position or posture of the sensor 12 compared to measurements performed through the measurement unit 13.

[0045] The defect area detection unit 15 confirms the absence of defective areas based on the measurement data supplemented by the measurement data completion unit 16. If a defective area is detected again in the defect area detection unit 15, the measurement data completion unit 16 performs another measurement to complete the measurement data. If no defective area is confirmed, the measurement data completion unit 16 outputs the measurement data.

[0046] The machining area determination unit 17 determines the additional area or cutting area that serves as the machining area based on the second reference model and the completed measurement data. The second reference model is pre-stored in the storage unit 18. The second reference model is either a 3D model or a 2D model. The machining area determination unit 17 compares the second reference model and the measurement data read from the storage unit 18.

[0047] When determining an additional region, the machining region determination unit 17 overlaps the measurement data with the second reference model, and determines the region that exists in the second reference model but not in the measurement data as the additional region. When determining a cutting region, the machining region determination unit 17 overlaps the measurement data with the second reference model, and determines the region that exists in the measurement data but not in the second reference model as the cutting region. The machining region determination unit 17 may also determine the additional region or the cutting region using other methods.

[0048] Next, the hardware structure of the processing unit used to implement the measuring device 10 will be described. Figure 2 This diagram illustrates an example of the hardware structure of the processing unit used to implement the measuring device 10 according to Embodiment 1. The processing unit of the measuring device 10, namely the measurement condition setting unit 11, the measurement unit 13, the measurement data merging unit 14, the defect area detection unit 15, the measurement data completion unit 16, and the processing area determination unit 17, is implemented using a processing circuit 80. The processing circuit 80 includes a processor 82 and a memory 83.

[0049] Processor 82 is a CPU (Central Processing Unit). Processor 82 can be a computing device, microprocessor, microcomputer, or DSP (Digital Signal Processor). Memory 83 is, for example, RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), etc.

[0050] The program for operating as the processing unit of the measuring device 10 is stored in the memory 83. The processing circuit 80 reads the program from the processor 82 and executes it, thereby enabling the function of the processing unit. The input unit 81 is a circuit that receives input signals 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 signals generated by the processing unit of the measuring device 10. The output unit 84 outputs data indicating the determined processing area.

[0051] Figure 2 The structure shown is an example of hardware where the processing unit of the measuring device 10 is implemented using a general-purpose processor 82 and memory 83. However, the processor 82 and memory 83 can be replaced by a dedicated processing circuit to implement the processing unit of the measuring device 10. The dedicated processing circuit can be a single circuit, a composite circuit, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a combination thereof. Alternatively, a portion of the processing unit can be implemented using the processor 82 and memory 83, while the remainder can be implemented using a dedicated processing circuit.

[0052] Next, the processing performed by the measuring device 10 will be described. Figure 3 This is a first flowchart illustrating the sequence of processes performed by the measuring device 10 according to Embodiment 1. Figure 3 The diagram shows the sequence of processes when the measuring device 10 determines the additional area.

[0053] In step S1, the measuring device 10 sets the measurement conditions via the measurement condition setting unit 11. The measurement condition setting unit 11 sets measurement conditions such as the settable range, measurement distance, observation angle, and exposure time in accordance with the state of the object.

[0054] The measuring device 10 acquires image information by capturing images of the object using the sensor 12. In step S2, the measuring 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 merges the measurement data using the measurement data merging unit 14. The measurement data merging unit 14 merges the measurement data acquired through multiple captures.

[0055] In step S4, the defect area detection unit 15 of the measuring device 10 detects the defect area based on the merged measurement data from step S3. In step S5, the measurement data completion unit 16 of the measuring device 10 remeasures the shape of the object to complete the measurement data. In step S6, the processing area determination unit 17 of the measuring device 10 determines the additional area based on the completed measurement data from step S5. The measuring device 10 then concludes its operation. Figure 3 The sequence of processes shown.

[0056] Figure 4 This is a second flowchart illustrating the sequence of processes performed by the measuring device 10 according to Embodiment 1. Figure 4 The diagram shows the processing sequence when the measuring device 10 determines the cutting area. Figure 4 The order of steps S1 to S5 shown is the same as Figure 3 The order of steps S1 to S5 shown is the same. If the measuring device 10 ends... Figure 4 Step S5, as shown, will then proceed sequentially to step S7.

[0057] In step S7, the machining area determination unit 17 of the measuring device 10 determines the cutting area based on the measurement data completed in step S5. The measuring device 10 then concludes its operation. Figure 4 The sequence of processes shown.

[0058] According to Embodiment 1, the measuring device 10 detects areas in the object where measurement data is missing, i.e., defective areas. Based on image information obtained through a re-capture by the sensor 12, the measuring device 10 remeasures the shape of the object, thereby obtaining remeasurement data related to the defective areas, and completes the measurement data using this remeasurement data. By completing the measurement data, the measuring device 10 can accurately determine the processing area for objects of various shapes or sizes.

[0059] As described above, the measuring device 10, having an object for adding or cutting material, can accurately determine the processing area for adding or cutting. The measuring device 10 is suitable for processing complex parts, such as vehicle parts, aerospace parts like turbines, or other aerospace components. The measuring device 10 improves the efficiency of changeover operations for determining the addition or cutting area. It shortens the time required for changeover operations and reduces the costs associated with them.

[0060] Implementation method 2.

[0061] In Embodiment 2, a structural example of the defect detection unit 15 and a structural example of the measurement data completion unit 16 will be described. Figure 5 This diagram illustrates a structural example of the defect detection unit 15 included in the measuring device 10 according to Embodiment 2. The defect detection unit 15 includes a defect candidate point detection unit 21, a contour extraction unit 22, an area calculation unit 23, and a defect determination unit 24.

[0062] The defect candidate point detection unit 21 detects defect candidate points based on the measurement data obtained by the measurement unit 13. Defect candidate points are candidates for points contained within the outline of the defect region. The defect candidate point detection unit 21 detects defect candidate points based on 3D point group data, which serves as the measurement data. The defect candidate point detection unit 21 determines the point of interest from the 3D point group data. For each point in the point group that is near the point of interest, i.e., a neighboring point, the defect candidate point detection unit 21 calculates the angle formed by the vector from the point of interest toward the first neighboring point and the vector from the point of interest toward the second neighboring point. Using the vector from the point of interest toward the first neighboring point as (a1, a2, a3) and the vector from the point of interest toward the second neighboring point as (b1, b2, b3), the defect candidate point detection unit 21 calculates the angle θ expressed by the following formula (1).

[0063] Formula 1

[0064]

[0065] The defect candidate point detection unit 21 generates a histogram of the calculated angle θ. If the histogram is centered around an angle larger than a certain reference angle, the defect candidate point detection unit 21 determines that the point of interest is a defect candidate point. Conversely, if the histogram is centered around an angle smaller than the reference angle, the defect candidate point detection unit 21 determines that the point of interest is not a defect candidate point. The defect candidate point detection unit 21 determines whether all point pairs in the 3D point group data are defect candidate points, thereby detecting defect candidate points based on the 3D point group data. Furthermore, the defect candidate point detection unit 21 can also change the reference angle according to the shape of the object. Additionally, the method for detecting defect candidate points is not limited to the method described in Embodiment 2, and can be any method.

[0066] The contour extraction unit 22 extracts contours containing candidate defect points from the data of candidate defect points. For example, the contour extraction unit 22 projects the candidate defect points onto a plane and performs edge extraction using methods such as the Canny method, thereby extracting the contour. The contour extraction unit 22 can extend the Canny method to 3D to perform edge extraction from 3D data, thereby extracting the contour. Furthermore, the method for extracting contours containing candidate defect points is not limited to the method described in Embodiment 2, and can be any method.

[0067] The area calculation unit 23 calculates the area of ​​the region enclosed by the contour extracted by the contour extraction unit 22. For example, the area calculation unit 23 projects the contour onto a plane, marks the region enclosed by the contour, and thereby calculates the area. Furthermore, the method for calculating the area of ​​the region enclosed by the contour is not limited to the method described in Embodiment 2, and can be any method.

[0068] The defect determination unit 24 determines whether the area enclosed by the contour extracted by the contour extraction unit 22 is a defective 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 to determine whether it is a defective area. If the calculated area is greater than or equal to the threshold, the defect determination unit 24 determines that the area enclosed by the contour is a defective area and outputs the area enclosed by the contour as a defective area. If the calculated area is less than the threshold, the defect determination unit 24 determines that the area enclosed by the contour is not a defective area. Furthermore, the defect determination unit 24 can change the area threshold according to the shape of the object. Also, the method for determining whether an area is a defective area is not limited to the method described in Embodiment 2, and can be any method.

[0069] Figure 6 This diagram illustrates a structural example of the measurement data complement 16 included in the measuring device 10 according to Embodiment 2. The measurement data complement 16 includes a normal distribution calculation unit 25, a position and attitude calculation unit 26, a re-measurement unit 27, and a re-merging unit 28.

[0070] The normal distribution calculation unit 25 calculates the distribution of the orientation of normals in the defect area detected by the defect area detection unit 15, i.e., the normal distribution. For example, the normal distribution calculation unit 25 determines the center point of the defect area and calculates a triangular facet by connecting the center point to two points among multiple points on the contour. The normal distribution calculation unit 25 estimates the triangular facet, i.e., the plane. For example, if the defect area is represented by a quadrilateral, four triangular facets are calculated. The plane is represented by the following equation (2).

[0071]

Formula 2

[0072] ax + by + cz + d = 0…(2)

[0073] Using equation (2), the normal vector of the triangular facet is represented as (a, b, c). The normal distribution calculation unit 25 calculates (a, b, c) as parameters representing the normals for multiple triangular faces, and can calculate the normal distribution based on the calculated parameters. Furthermore, the method for calculating the normal distribution is not limited to the method described in embodiment 2, and can be any method.

[0074] The position and attitude calculation unit 26 calculates the position or attitude of an object where the sensor 12 and the object are directly opposite each other, or the position or attitude of the sensor 12, based on the normal distribution. For example, the position and attitude calculation unit 26 calculates the frequency of normals greater than or equal to a preset threshold in the normals of the defective region. The position and attitude calculation unit 26 also calculates the position or attitude of an object where the orientation of the optical axis of the sensor 12 is close to the orientation of the calculated normals, or the position or attitude of the sensor 12. Furthermore, the method for calculating the position or attitude of an object where the sensor 12 and the object are directly opposite each other, or the position or attitude of the sensor 12, is not limited to the method described in Embodiment 2, and can be any method. Here, "sensor 12 and the object are directly opposite each other" does not necessarily mean that the object and the sensor 12 are directly facing each other. The defective region detected by the defective region detection unit 15 only needs to be included in the area that can be obtained by the sensor 12, and the object and the sensor 12 do not need to be directly opposite each other. "Sensor 12 and the object are directly opposite each other" includes the case where the object and the sensor 12 are not directly opposite each other.

[0075] The remeasurement unit 27 remeasures the shape of the object based on the position or orientation of the object, or image information obtained by re-capturing the object through the sensor 12 after the position or orientation of the sensor 12 has been corrected. Based on the calculation results obtained by the position and orientation calculation unit 26, the remeasurement unit 27 corrects at least one of the object's position, object's orientation, sensor 12's position, and sensor 12's orientation. The remeasurement unit 27 remeasures the shape of the object, thereby obtaining remeasurement data related to the defective area.

[0076] The re-merging unit 28 merges the re-measurement data obtained by the re-measurement unit 27 with the measurement data obtained by the measurement unit 13. If the re-measurement data contains unwanted data, such as data related to the background of the object, the re-merging unit 28 can use a background subtraction method to remove the unwanted background data. Therefore, the re-merging unit 28 can merge only the re-measurement data related to the object with the measurement data.

[0077] When merging the remeasurement data with the measurement data, the re-merging unit 28 calculates the completion rate, which represents the ratio of the measurement data in the missing area to the completed data. If the calculated completion rate exceeds a preset threshold, the measuring device 10 completes the measurement data completion performed by the measurement data completion 16. If the calculated completion rate does not exceed the threshold, the measuring 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 16.

[0078] Next, the processing implemented by the defect area detection unit 15 and the measurement data completion unit 16 will be explained. Figure 7 This is a flowchart showing the sequence of processing performed by the defect detection unit 15 and the measurement data completion unit 16 of the measuring device 10 according to Embodiment 2.

[0079] In step S11, the defect candidate point detection unit 21 of the defect region detection unit 15 detects defect candidate points based on the 3D point group data used as measurement data. In step S12, the contour extraction unit 22 of the defect region detection unit 15 extracts the contour containing the defect candidate points detected in step S11. In step S13, the area calculation unit 23 of the defect region detection unit 15 calculates the area of ​​the region enclosed by the contour extracted in step S12.

[0080] In step S14, the defect determination unit 24 of the defect area detection unit 15 determines whether the area enclosed by the contour is a defect area. The defect determination unit 24 compares the calculated area with a preset threshold to determine whether it is a defect area. If it is determined that the area enclosed by the contour is not a defect area (step S14, No), the defect area detection unit 15 and the measurement data completion 16 end. Figure 7 The processing involved in the sequence shown. On the other hand, if it is determined that the area surrounded by the contour is a defective area (step S14, Yes), the defective area detection unit 15 and the measurement data completion unit 16 proceed to step S15.

[0081] In step S15, the normal distribution calculation unit 25 of the measurement data completion 16 calculates the normal distribution of the defective area. In step S16, the position and attitude calculation unit 26 of the measurement data completion 16 calculates the position or attitude of the sensor 12 facing the object, or the position or attitude of the sensor 12.

[0082] In step S17, the remeasurement unit 27 of the measurement data completion unit 16 corrects the position or orientation of the object or the position or orientation of the sensor 12 and remeasures the shape of the object to obtain remeasurement data. In step S18, the remerging unit 28 of the measurement data completion unit 16 merges the remeasurement data obtained in step S17 with the measurement data.

[0083] In step S19, the re-merging unit 28 determines whether the completion rate of the measurement data exceeds a threshold. If the completion rate of the measurement data does not exceed the threshold (step S19, No), the defect area detection unit 15 and the measurement data completion unit 16 will sequentially return to step S11 to repeat the defect area detection and measurement data completion. On the other hand, if the completion rate of the measurement data exceeds the threshold (step S19, Yes), the defect area detection unit 15 and the measurement data completion unit 16 will end. Figure 7 The sequence of processes shown.

[0084] According to Embodiment 2, the defect detection unit 15 detects candidate defect points and extracts the contour containing the candidate defect points. The defect detection unit 15 determines whether a region enclosed by the contour is a defect region based on the area of ​​the region enclosed by the contour, thereby enabling defect detection. Furthermore, the measurement data completion unit 16 calculates the normal distribution of the defect region, calculating the position or orientation of the object (such as the sensor 12 facing the object) or the position or orientation of the sensor 12. After the position or orientation of the object or the position or orientation of the sensor 12 is corrected, the measurement data completion unit 16 obtains remeasurement data by re-measuring the object and merges the remeasurement data with the measurement data. As described above, the measuring device 10 can complete the measurement data regarding defect regions. The measuring device 10 has the effect of accurately determining the processing area for adding or cutting materials to an object.

[0085] Implementation method 3.

[0086] In Embodiment 3, a structural example of the measurement condition setting unit 11 will be described. Figure 8 This diagram illustrates a structural example of the measurement condition setting unit 11 included in the measuring device 10 according to Embodiment 3. 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.

[0087] The range adjustment unit 31 adjusts the settable range that allows setting the object and sensor 12 when acquiring image information. 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 acquiring image information. 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 settable 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. Detailed descriptions of the structures of the range adjustment unit 31, the measurement distance adjustment unit 32, and the exposure time adjustment unit 33 will be provided later.

[0088] Next, the processing implemented by the measurement condition setting unit 11 will be explained. Figure 9 This is a flowchart showing the sequence of processes performed by the measurement condition setting unit 11 of the measuring device 10 according to Embodiment 3.

[0089] In step S21, the range adjustment unit 31 of the measurement condition setting unit 11 adjusts the settable 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. The measurement condition setting unit 11 then concludes its operation. Figure 9 The processing involved in the sequence shown is detailed below. The 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.

[0090] Figure 10 This diagram illustrates a structural example of the range adjustment unit 31 included in the measurement condition setting unit 11 of Embodiment 3. The range adjustment unit 31 includes a scene generation unit 34, an interference determination unit 35, and a range determination unit 36.

[0091] The scene generation unit 34 configures the object, sensor 12, and components surrounding the object or sensor 12 in an imaginary space, thereby simulating the scene when the object is photographed. The scene generation unit 34 obtains a first reference model from the storage unit 18. The scene generation unit 34 configures the object, sensor 12, and components represented by the first reference model in the imaginary space. For example, when the object is rotated by a rotary table, the rotary table and its drive unit can include components surrounding the object. The conditions for simulating the scene generation are manually set by the user of the measuring device 10. The scene generation unit 34 automatically sets the conditions based on pre-prepared default values ​​or preset values.

[0092] The interference determination unit 35 determines whether there is interference between the object or the sensor 12 and the component when at least one of the following changes occurs in the scene: the position of the object, the orientation of the object, the position of the sensor 12, and the orientation of the sensor 12.

[0093] The direction of position change of the object and the direction of position change of the sensor 12 can be set to any of the X-axis, Y-axis, and Z-axis directions. The rotation axis used to change the attitude of the object and the rotation axis used to change the attitude of the sensor 12 can be set to any of the A-axis, B-axis, and C-axis. The A-axis, B-axis, and C-axis are set as three mutually perpendicular rotation axes. The direction of position change of the object, the direction of position change of the sensor 12, the rotation axis used to change the attitude of the object, and the rotation axis used to change the attitude of the sensor 12 are manually set by the user of the measuring device 10. The interference determination unit 35 can automatically set the direction of position change of the object, the direction of position change of the sensor 12, the rotation axis used to change the attitude of the object, and the rotation axis used to change the attitude of the sensor 12 based on pre-prepared default values ​​or preset values.

[0094] The range determination unit 36 ​​determines the settable range of the object and the sensor 12 based on the determination result obtained by the interference determination unit 35. For example, the range determination unit 36 ​​determines the settable range as the range within which the object and the sensor 12 will not interfere with the object or components surrounding the sensor 12. As described above, the measurement condition setting unit 11 determines the settable range in the range determination unit 36, thereby setting one settable range for the measurement conditions. With the object and the sensor 12 positioned within the settable range, the sensor 12 captures an image of the object, and the measurement unit 13 measures the object.

[0095] The position or orientation of the object at the start of the measurement performed by the measuring unit 13, or the position or orientation of the sensor 12, is manually determined by the user based on a set settable range. Alternatively, the position or orientation of the object at the start of the measurement performed by the measuring unit 13, or the position or orientation of the sensor 12, can be automatically determined by the measuring unit 13 based on a settable range.

[0096] Figure 11 This diagram illustrates a structural example of the measurement distance adjustment unit 32 included in the measurement condition setting unit 11 of Embodiment 3. The measurement distance adjustment unit 32 includes a point group number acquisition unit 37 and a measurement distance determination unit 38.

[0097] The point group number acquisition unit 37 acquires the number of points contained in the 3D point group data acquired by the sensor 12, i.e., the point group number. For example, the point group number acquisition unit 37 simulates the imaging of the first reference model in imaginary space, thereby acquiring the point group number of the first reference model. The point group number acquisition unit 37 acquires the point group number while changing the measurement distance within a settable range set by the range adjustment unit 31, thereby acquiring the point group number in units of measurement distance. The point group number acquisition unit 37 can acquire the point group number while changing the measurement distance and the observation angle of the sensor 12, thereby acquiring the point group number corresponding to the measurement distance and the observation angle.

[0098] The measurement distance determination unit 38 determines the measurement distance for shooting the object based on the number of point groups obtained by the point group number acquisition unit 37 in units of measurement distance. For example, the measurement distance determination unit 38 compares the number of point groups in units of measurement distance with each other and determines the measurement distance at which the number of point groups is the largest as the measurement distance for shooting. When the point group number acquisition unit 37 obtains a number of point groups corresponding to the measurement distance and observation angle, the measurement distance determination unit 38 can determine the measurement distance and observation angle for shooting based on the number of point groups obtained corresponding to the measurement distance and observation angle.

[0099] As described above, the measurement condition setting unit 11 determines the measurement distance in the measurement distance determination unit 38, thereby setting one of the measurement conditions, namely the measurement distance. The sensor 12 takes a picture of the object at the set measurement distance, and the measurement unit 13 measures the object. Furthermore, the method for setting the measurement distance is not limited to the method described in Embodiment 3, and can be any method.

[0100] Figure 12 This diagram illustrates a structural example of the exposure time adjustment unit 33 included in the measurement condition setting unit 11 of 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.

[0101] The reflectivity distribution acquisition unit 39 acquires the reflectivity distribution of the object. For example, the reflectivity distribution acquisition unit 39 takes pictures of the object and a reflector with known reflectivity using the sensor 12 under the same environment, and calculates the reflectivity distribution of the object based on the measurement results of the brightness value of the reflector. Furthermore, the method for acquiring the reflectivity distribution of the object is not limited to the method described in Embodiment 3, and can be any method.

[0102] The lookup table stored in storage unit 18 contains a database that aggregates reflectance distribution data related to various types of objects. The lookup table includes reflectance distribution data related to objects with relatively high gloss and reflectance distribution data related to objects with relatively low gloss. The reflectance distribution data related to various types of objects is obtained in advance, for example, based on the results of photographing objects by sensor 12, and stored in the lookup table.

[0103] The data comparison unit 40 compares the reflectance distribution of the object with the reflectance distribution data pre-stored in a lookup table. Through this comparison, 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.

[0104] The data comparison unit 40 calculates, for example, the similarity between the reflectance distribution of an object and the reflectance distribution pre-stored in a lookup table using the following equation (3). g(M) represents the data of the reflectance distribution of the object. g(P) represents the data of the reflectance distribution of a certain object pre-stored in the lookup table. The smaller the value shown in equation (3), the higher the similarity between the reflectance distribution of the object and the reflectance distribution of the object in g(P).

[0105]

Formula 3

[0106] argmin P (g(M)-g(P))…(3)

[0107] In the lookup table, the data on the reflectance distribution for each object is associated with values ​​of parameters related to the measurement performed using sensor 12. These measurement-related parameters include, for example, exposure time or gain. The data on the reflectance distribution for each object is associated with values ​​of parameters suitable for the measurement of that object performed by sensor 12. These suitable parameter values ​​are predetermined, for example, based on the results of the image captured by sensor 12 of the object.

[0108] The exposure time determination unit 41 determines the exposure time of the sensor 12 based on the comparison result obtained by the data comparison unit 40. The exposure time determination unit 41 selects the data of the reflectance distribution that has the highest similarity to the reflectance distribution of the object from 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 for shooting. Furthermore, the values ​​of parameters other than the exposure time among the measurement-related parameters can be determined in the same way as the exposure time. The exposure time determination unit 41 can determine the gain associated with the selected reflectance distribution data as the gain for shooting.

[0109] As described above, the measurement condition setting unit 11 determines the exposure time in the exposure time determination unit 41, thereby setting one of the measurement conditions, namely the exposure time. The sensor 12 takes a picture of the object at the set exposure time, and the measurement unit 13 measures the object. Furthermore, the method for setting the exposure time is not limited to the method described in Embodiment 3, and can be any method.

[0110] Next, the processing performed by the range adjustment unit 31, the measurement distance adjustment unit 32, and the exposure time adjustment unit 33 will be explained. Figure 13 This is a flowchart showing the sequence of processes performed by the range adjustment unit 31, the measurement distance adjustment unit 32, and the exposure time adjustment unit 33 of the measuring device 10 according to Embodiment 3.

[0111] In step S31, the scene generation unit 34 of the range adjustment unit 31 simulates the scene during object shooting. In step S32, the interference determination unit 35 of the range adjustment unit 31 determines whether there is interference between the object or the sensor 12 and the component in the scene generated in step S31. In step S33, the range determination unit 36 ​​of the range adjustment unit 31 determines the settable range of the object and the sensor 12 based on the determination result in step S32.

[0112] In step S34, the point group number acquisition unit 37 of the measurement distance adjustment unit 32 acquires the point group number. In step S35, the measurement distance determination unit 38 of the measurement distance adjustment unit 32 determines the measurement distance for shooting the object based on the point group number acquired in step S34.

[0113] 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 for photographing the object based on the comparison result in step S37. This concludes the description of the range adjustment unit 31, the measurement distance adjustment unit 32, and the exposure time adjustment unit 33. Figure 13 The sequence of processes shown.

[0114] According to Embodiment 3, the measurement condition setting unit 11 sets the settable range, measurement distance, and exposure time when acquiring image information. The measuring device 10 can set measurement conditions suitable for measuring the object by the measuring unit 13. As described above, the measuring device 10 has the effect of accurately determining the processing area for adding or cutting materials related to the object.

[0115] Implementation method 4.

[0116] In Embodiment 4, an example of the structure of the processing area determination unit 17 will be described. Figure 14 This diagram illustrates a structural example of the processing area determination unit 17 included in the measuring device 10 according to Embodiment 4. The processing area determination unit 17 includes a noise removal unit 51, an alignment unit 52, and a processing area determination unit 53.

[0117] The noise removal unit 51 removes noise from the measurement data after it has been completed by the measurement data completion unit 16. For example, the noise removal unit 51 sets a threshold for each coordinate of the 3D point group data that is used as measurement data, and treats data that falls outside the range defined by the threshold as noise and removes the noise.

[0118] When the object has a simple shape such as a cuboid, the noise removal unit 51 can estimate the shape of the planar combination, i.e., the primitive shape, and remove data that deviates from the estimated primitive shape as noise. The noise removal unit 51 can remove data that deviates from the primitive shape in the measurement data using the RANSAC (RANdom SAmple Consensus) method. The noise removal unit 51 can perform statistical processing on the 3D point group data and remove noise based on the statistical values. Furthermore, the method for removing noise is not limited to the method described in Embodiment 4, and can be any method.

[0119] The alignment unit 52 aligns the measurement data after noise removal by the noise removal unit 51 with the model of the finished product obtained by attachment or cutting, i.e., the second reference model. The alignment unit 52 performs alignment based on ICP (Iterative Closest Point) or alignment based on feature points.

[0120] In addition to aligning the measurement data with the second reference model as a whole via ICP or the like, the alignment unit 52 can also specify a portion of the second reference model and perform alignment using that specified portion as a reference. For example, when the object has a complex or special shape, or when the object is a large-sized product compared to the finished product, the alignment unit 52 can use a specific portion of the object, such as the part that has been cut off, as a reference for alignment. The alignment result performed by the alignment unit 52 can be manually fine-tuned by the user. Furthermore, the alignment method is not limited to the method described in Embodiment 4, and can be any method.

[0121] The machining area determination unit 53 determines the additional area or cutting area, i.e., the machining area, based on the measurement data after alignment by the alignment unit 52 and the second reference model. The machining area determination unit 53 calculates the difference between the measurement data and the second reference model, thereby determining the machining area.

[0122] When determining additional regions, the processing region determination unit 53 subtracts the 3D point group data from the second reference model to obtain the difference; that is, regions existing in the second reference model but not in the 3D point group data are determined as additional regions. For example, the processing region determination unit 53 calculates the difference between vertices and 3D point group data in the second reference model, and outputs the calculation result of the difference at the vertices as data representing the determined additional regions. The processing region determination unit 53 can output both the calculation result of the difference at the vertices and the two types of mesh data as data representing the determined additional regions. If the second reference model has few vertices, making it difficult to represent the additional regions using the calculation result of the difference at the vertices, the processing region determination unit 53 can calculate the difference between the 3D point group data (which is the second reference model) and the 3D point group data (which is the measurement data) after transforming the second reference model into 3D point group data. As described above, the processing region determination unit 17 determines the additional regions through the processing region determination unit 53, thereby determining the additional regions. Furthermore, the method for determining the additional regions is not limited to the method described in Embodiment 4, and can be any method.

[0123] When determining the cutting area, the machining area determination unit 53 subtracts the second reference model from the 3D point group data to obtain the difference; that is, the area that exists in the 3D point group data but not in the second reference model is determined as the cutting area. For example, the machining area determination unit 53 calculates the difference between the 3D point group data and the vertices in the second reference model, and outputs the calculation result of the difference at the vertices as data representing the determined cutting area. The machining area determination unit 53 can output the calculation result of the difference at the vertices and two types of data (mesh) as data representing the determined cutting area. If the second reference model has few vertices, making it difficult to represent the cutting area using the calculation result of the difference at the vertices, the machining area determination unit 53 can calculate the difference between the 3D point group data (as measurement data) and the 3D point group data (as the second reference model) after transforming the second reference model into 3D point group data. As described above, the machining area determination unit 17 determines the cutting area through the machining area determination unit 53, thereby determining the cutting area. Furthermore, the method for determining the cutting area is not limited to the method described in Embodiment 4, and can be any method.

[0124] Next, the processing performed by the processing area determination unit 17 will be explained. Figure 15 This is a first flowchart illustrating the sequence of processes performed by the processing area determination unit 17 of the measuring device 10 according to Embodiment 4. Figure 15 The diagram shows the processing sequence when the processing area determination unit 17 determines the additional area.

[0125] In step S41, the noise removal unit 51 of the processing area determination unit 17 removes noise from the measurement data supplemented by the measurement data supplement 16. In step S42, the alignment unit 52 of the processing area determination unit 17 aligns the noise-removed measurement data from step S41 with the model of the finished product obtained by attachment, i.e., the second reference model.

[0126] In step S43, the processing area determination unit 53 of the processing area determination unit 17 determines the additional area based on the measurement data after alignment in step S42 and the second reference model. The processing area determination unit 17 then concludes its process. Figure 15 The sequence of processes shown.

[0127] Figure 16 This is a second flowchart illustrating the sequence of processes performed by the processing area determination unit 17 of the measuring device 10 according to Embodiment 4. Figure 16 The diagram shows the processing sequence when the machining area determination unit 17 determines the cutting area.

[0128] Figure 16 The order of steps S41 and S42 shown is the same as... Figure 15 The order of steps S41 and S42 shown is the same. If the processing area determination unit 17 ends... Figure 16 Step S42, as shown, will then proceed sequentially to step S44.

[0129] In step S44, the machining area determination unit 53 of the machining area determination unit 17 determines the cutting area based on the measurement data after alignment in step S42 and the second reference model. The machining area determination unit 17 then concludes its process. Figure 16 The sequence of processes shown.

[0130] According to Embodiment 4, the processing area determination unit 17 performs alignment of the measurement data and the second reference model after removing noise from the measurement data, and determines the processing area. The measuring device 10 can accurately determine the processing area through the processing area determination unit 17. As described above, the measuring device 10 has an object related to the addition or cutting of the material, and can accurately determine the processing area for the addition or cutting.

[0131] Implementation method 5.

[0132] In Embodiment 5, an additional processing system having a measuring device 10 will be described. Figure 17This is a diagram illustrating a structural example of the auxiliary processing system 60 according to Embodiment 5. The auxiliary processing system 60 includes a measuring device 10, a mesh generation device 61, a computer-aided manufacturing (CAM) device 62, and an auxiliary processing device 63.

[0133] The measuring device 10 measures the shape of the object, thereby determining the additional area to be added. The measuring device 10 of the additional processing system 60 can be any of the measuring devices 10 described in embodiments 1 to 4. The mesh generation device 61 generates a mesh model. The CAM device 62 generates a processing path for adding material to the object and generates a processing program. The additional processing device 63 is a machine that manufactures a shape by adding material to the object.

[0134] Mesh generation device 61 is a computer system equipped with a program for generating mesh models. CAM device 62 is a computer system equipped with CAM software. CAM software is used to generate machining paths and machining programs. The functions of mesh generation device 61 and CAM device 62 are similar. Figure 2 Similarly, the hardware structure shown is implemented using a processing circuit 80 having a processor 82 and a memory 83.

[0135] Mesh generation device 61 generates meshes generated by... Figure 1 The mesh model of the additional region determined by the processing area determination unit 17 is shown. The mesh generation device 61, for example, acquires 3D point group data representing the additional region and generates a mesh model based on the 3D point group data. The mesh generation device 61 can receive the result determined by the processing area determination unit 17 and use it as part of the mesh data of the finished product model, i.e., the second reference model, and generate a mesh model only for a portion of the missing mesh areas.

[0136] The CAM device 62 calculates the machining path based on the mesh model generated by the mesh generation device 61, transforms the machining path into a machining program, and thereby generates the machining program. The auxiliary machining device 63 manufactures the object according to the machining program generated by the CAM device 62.

[0137] The auxiliary processing device 63 applies material molten by irradiation with a light beam to an object, thereby creating a shape. The light beam, serving as the heat source, can be a laser beam or an electron beam, etc. An electric arc can be used instead of a light beam as the heat source. The auxiliary processing device 63 can be equipped with peripheral equipment such as devices for monitoring the shape during manufacturing or for measuring temperature or oxygen concentration within the auxiliary processing device 63. Figure 17 The figure shows an additional machining system 60 with an additional machining device 63. Figure 17The illustrated auxiliary processing system 60 manufactures a shape using one auxiliary processing device 63. The auxiliary processing system 60 may have multiple auxiliary processing devices 63, and shapes can be manufactured using multiple auxiliary processing devices 63.

[0138] Next, the operation of the auxiliary machining system 60 will be explained. Figure 18 This is a flowchart illustrating the sequence of operations of the additional processing system 60 according to Embodiment 5. In step S51, the measuring device 10 of the additional processing system 60 measures the shape of the object, thereby determining the additional area. The measuring device 10, through... Figure 3 The additional regions are determined in the same order shown.

[0139] In step S52, the mesh generation device 61 of the additional processing system 60 generates a mesh model of the additional region determined in step S51. In step S53, the CAM device 62 of the additional processing system 60 generates a processing path and processing program based on the mesh model generated in step S52. In step S54, the additional processing device 63 of the additional processing system 60 manufactures the object by adding material to it. The additional processing system 60 then concludes. Figure 18 The sequence of actions shown.

[0140] According to embodiment 5, the additional processing system 60 includes a measuring device 10, which enables accurate determination of the additional area. The additional processing system 60's ability to accurately determine the additional area allows for the manufacture of high-precision shapes. Furthermore, the additional processing system 60 consistently performs the process from measuring the object to manufacturing the shape, thereby improving the efficiency of changeover operations until the shape is manufactured. The additional processing system 60 can shorten the time required for changeover operations and reduce the costs associated with them. The additional processing system 60 can reduce the time and costs required from the introduction of the additional processing device 63 to the verification of the manufactured shape.

[0141] Implementation method 6.

[0142] In Embodiment 6, a cutting system having a measuring device 10 will be described. Figure 19 This is a diagram illustrating a structural example of the cutting system 70 according to Embodiment 6. The cutting system 70 includes a measuring device 10, a mesh generation device 71, a CAM device 72, a cutting device 73, and an auxiliary processing device 74.

[0143] The measuring device 10 measures the shape of the object, thereby determining the cutting area where cutting is performed. The measuring device 10 of the cutting system 70 can be any of the measuring devices 10 described in embodiments 1 to 4. In embodiment 6, the object is a shaped object manufactured by the additional processing device 74.

[0144] Mesh generation device 71 generates a mesh model. CAM device 72 generates a machining path for cutting the object and generates a machining program. Cutting machining device 73 is a machine tool that manufactures workpieces through cutting.

[0145] Mesh generation device 71 is a computer system equipped with a program for generating mesh models. CAM device 72 is a computer system equipped with CAM software. CAM software is a program used to generate machining paths and machining programs. The functions of mesh generation device 71 and CAM device 72 are similar. Figure 2 Similarly, the hardware structure shown is implemented using a processing circuit 80 having a processor 82 and a memory 83.

[0146] Mesh generation device 71 generates meshes from... Figure 1 The mesh model of the cutting area determined by the machining area determination unit 17 is shown. The mesh generation device 71 can generate a mesh model based on the measurement data obtained by aligning the machining area determination unit 17 with the second reference model.

[0147] The CAM device 72 calculates the machining path based on the mesh model generated by the mesh generation device 71, transforms the machining path into a machining program, and thereby generates the machining program. The CAM device 72 can utilize data representing the difference between the result determined by the machining area determination unit 17 and the second reference model, which serves as the finished product model, during the generation of the machining path and the machining program. The cutting machining device 73 performs cutting machining according to the machining program generated by the CAM device 72.

[0148] The auxiliary processing device 74 applies material that has been melted by the irradiation of a light beam, thereby creating a shape. The shape created by the auxiliary processing device 74 is then conveyed to the cutting processing device 73.

[0149] The cutting processing apparatus 73 manufactures a workpiece by cutting a shaped object. Peripheral equipment, such as devices for monitoring the workpiece during the cutting process, can be installed in the cutting processing apparatus 73. Figure 19 The diagram shows a cutting system 70 with one cutting device 73. Figure 19The cutting system 70 shown manufactures a workpiece through cutting by a single cutting device 73. The cutting system 70 may have multiple cutting devices 73, and workpieces may be manufactured through cutting by multiple cutting devices 73.

[0150] Next, the operation of the cutting system 70 will be explained. Figure 20 This is a flowchart illustrating the operation sequence of the cutting system 70 according to Embodiment 6. In step S61, the measuring device 10 of the cutting system 70 measures the shape of the object, thereby determining the cutting area. The object is a shape manufactured by the auxiliary processing device 74. The measuring device 10, through... Figure 4 The cutting area is determined in the same order shown.

[0151] In step S62, the mesh generation device 71 of the cutting system 70 generates a mesh model of the cutting area determined in step S61. In step S63, the CAM device 72 of the cutting system 70 generates a machining path and machining program based on the mesh model generated in step S62.

[0152] In step S64, the cutting device 73 of the cutting system 70 manufactures a workpiece by cutting the object. The cutting system 70 then concludes. Figure 20 The sequence of actions shown.

[0153] According to Embodiment 6, the cutting system 70 includes a measuring device 10, thereby enabling accurate determination of the cutting area. The cutting system 70's ability to accurately determine the cutting area allows for high-precision manufacturing of the workpiece. Furthermore, the cutting system 70 continuously performs the process from measuring the object to manufacturing the workpiece, thereby improving the efficiency of changeover operations until the workpiece is manufactured. The cutting system 70 can shorten the time required for changeover operations and reduce the costs associated with them. The cutting system 70 can reduce the time and costs required from the introduction of the cutting device 73 to the verification of the workpiece's manufacturing.

[0154] Furthermore, in the cutting system 70, the object to which the cutting device 73 performs cutting is not limited to the shape manufactured by the auxiliary processing device 74. In the cutting system 70, the cutting device 73 can also cut objects other than those manufactured by the auxiliary processing device 74, thereby producing a processed product. The cutting system 70 may include at least the measuring device 10 and the cutting device 73. The cutting system 70 may also not include the auxiliary processing device 74.

[0155] Implementation method 7.

[0156] The mesh generation apparatuses 61 and 71 in Embodiment 5 or 6 can generate mesh models using learning algorithms such as neural networks. In Embodiment 7, the mesh generation apparatuses 61 and 71 that generate mesh models using neural networks will be described.

[0157] Input to the neural network Figure 1 The result determined by the machining area determination unit 17 is either data representing the additional region or data representing the cutting region. The neural network outputs a mesh model obtained through a pre-defined representation method based on the input data representing either the additional region or the cutting region. When the input data represents the additional region, the input data can be 3D point group data representing the additional region. When the input data represents the cutting region, the input data can be measurement data aligned with the second reference model. For example, a GAN (Generative Adversarial Network) can be used as the neural network.

[0158] Mesh generation devices 61 and 71 are capable of generating meshes with high performance through neural networks. Neural networks are expected to be more versatile than manually constructed mesh generation algorithms. Therefore, mesh generation devices 61 and 71 can generate mesh models for objects of various shapes and sizes.

[0159] Furthermore, the learning data input to the mesh generation devices 61 and 71, i.e., the input data, and the network structure possessed by the mesh generation devices 61 and 71, are not limited to those described in Embodiment 7. The learning data can be any data. In addition, any network structure can be used in the mesh generation devices 61 and 71.

[0160] The structures shown in the above embodiments illustrate one example of the content of the present invention. The structures of each embodiment can be combined with other known technologies. The structures of each embodiment can also be appropriately combined with each other. A portion of the structure of each embodiment can be omitted or modified without departing from the spirit of the present invention.

[0161] Explanation of the label

[0162] 10. Measuring device; 11. Measuring condition setting unit; 12. Sensor; 13. Measuring unit; 14. Measuring data merging unit; 15. Defect area detection unit; 16. Measuring data completion unit; 17. Processing area determination unit; 18. Storage unit; 21. Defect candidate point detection unit; 22. Contour extraction unit; 23. Area calculation unit; 24. Defect judgment unit; 25. Normal distribution calculation unit; 26. Position and attitude calculation unit; 27. Re-measurement unit; 28. Re-merging unit; 31. Range adjustment unit; 32. Measuring distance adjustment unit; 33. Exposure time adjustment unit; 34. Scene generation unit. 35 Interference determination unit, 36 Range determination unit, 37 Point group number acquisition unit, 38 Measurement distance determination unit, 39 Reflectivity 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 generation 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 measuring device, characterized in that, have: A sensor that acquires image information by photographing an object that has been subjected to material application or cutting. The measurement unit measures the shape of the object based on the image information, thereby obtaining measurement data representing the shape of the object; The defect area detection unit detects the area in the object where the measurement data is missing, i.e., the defect area. The measurement data is completed by re-measuring the shape of the object based on the image information obtained by re-capturing through the sensor, thereby obtaining measurement data related to the missing area, i.e., re-measurement data, and then completing the measurement data using the re-measurement data. as well as The processing area determination unit determines the processing area where the additional processing or cutting is performed, based on the model of the finished product obtained through the additional processing or cutting and the completed measurement data. The defect detection unit has: The defect candidate point detection unit detects candidate points, i.e. defect candidate points, of points contained in the contour of the defect region based on the measurement data obtained by the measurement unit. A contour extraction unit extracts the contour containing the candidate defect points from the data of the candidate defect points; An area calculation unit calculates the area of ​​the region enclosed by the outline; as well as The defect determination unit determines whether the area enclosed by the contour is the defect area based on the calculated area.

2. The measuring device according to claim 1, characterized in that, The measurement data complement has the following characteristics: The normal distribution calculation unit calculates the distribution of the orientation of the normals in the defect area detected by the defect area detection unit, i.e., the normal distribution. The position and attitude calculation unit calculates the position or attitude of the object, or the position or attitude of the sensor, based on the normal distribution, when the sensor and the object are facing each other. The remeasurement unit remeasures the shape of the object based on the position or orientation of the object, or image information obtained by re-capturing the object through the sensor after the position or orientation of the sensor has been corrected, thereby obtaining the remeasurement data; and The re-merging unit merges the remeasurement data with the measurement data.

3. The measuring device according to claim 1 or 2, characterized in that, It also includes a measurement condition setting unit, which sets the measurement conditions for the measurements performed by the measurement unit. The measurement condition setting unit has: The range adjustment unit adjusts the range within which the object and the sensor can be set when the image information is acquired; A distance adjustment unit adjusts the measurement distance of the sensor; as well as The exposure time adjustment unit adjusts the exposure time of the sensor.

4. The measuring device according to claim 3, characterized in that, The range adjustment unit has: The scene generation unit configures the object, the sensor, or components surrounding the object or the sensor in an imaginary space, thereby simulating the scene when the object is photographed. An interference determination unit determines whether there is interference between the object, the sensor, and the component when at least one of the position, orientation, position, and orientation of the object, is changed in the scene. as well as The range determination unit determines the range within which the object and the sensor can be set based on the determination result obtained by the interference determination unit.

5. The measuring device according to claim 3, characterized in that, The distance adjustment unit has: The point group acquisition unit acquires the number of points, i.e., the point group number, contained in the 3D point group data acquired by the sensor, using the distance from the object to the sensor (i.e., the measurement distance) as the unit; and The distance determination unit determines the measurement distance for photographing the object based on the number of points obtained in units of the measurement distance.

6. The measuring device according to claim 3, characterized in that, The exposure time adjustment unit has: A reflectance distribution acquisition unit acquires the reflectance distribution of the object. The data comparison unit compares the reflectance distribution with pre-saved reflectance distribution data; and The exposure time determination unit determines the exposure time based on the comparison results obtained by the data comparison unit.

7. The measuring device according to claim 1 or 2, characterized in that, The processing area determining unit has: The noise removal unit removes noise from the completed measurement data using the measurement data supplementation. The alignment section aligns the measurement data after the noise has been removed with the model. as well as The processing area determination unit determines the processing area based on the measurement data after the alignment and the model.

8. An additional processing system, characterized in that, have: Additional processing equipment that creates shapes by adding material to an object; A measuring device that measures the shape of the object, thereby determining the additional area to be implemented; Mesh generation apparatus, which generates a mesh model for the additional region; and A computer-aided manufacturing apparatus that generates a machining program based on the aforementioned grid model. The measuring device has: A sensor that acquires image information by photographing the object; The measurement unit measures the shape of the object based on the image information, thereby obtaining measurement data representing the shape of the object; The defect area detection unit detects the area in the object where the measurement data is missing, i.e., the defect area. The measurement data is completed by re-measuring the shape of the object based on the image information obtained through a second capture by the sensor, thereby obtaining measurement data related to the missing area, i.e., remeasurement data, and completing the measurement data using the remeasurement data; and The processing area determination unit determines the additional area based on a model representing the processed shape and the completed measurement data. The mesh generation device generates the mesh model of the additional region determined by the processing area determination unit. The additional processing device manufactures the shape according to the processing procedure.

9. The additional processing system according to claim 8, characterized in that, The mesh generation apparatus generates the mesh model using a neural network that outputs the mesh model based on input data representing the additional region determined by the processing region determination unit.

10. A cutting process system, characterized in that, have: A cutting processing device that manufactures processed products by cutting an object; A measuring device that measures the shape of the object, thereby determining the cutting area where the cutting is performed; Mesh generation apparatus, which generates a mesh model of the cutting region; and A computer-aided manufacturing apparatus that generates a machining program based on the aforementioned grid model. The measuring device has: A sensor that acquires image information by photographing the object; The measurement unit measures the shape of the object based on the image information, thereby obtaining measurement data representing the shape of the object; The defect area detection unit detects the area in the object where the measurement data is missing, i.e., the defect area. The measurement data is completed by re-measuring the shape of the object based on the image information obtained through a second capture by the sensor, thereby obtaining measurement data related to the missing area, i.e., remeasurement data, and completing the measurement data using the remeasurement data; and The machining area determination unit determines the cutting area based on a model representing the machined shape and the completed measurement data. The mesh generation device generates the mesh model of the cutting area determined by the machining area determination unit. The cutting apparatus manufactures the workpiece according to the processing procedure.

11. The cutting system according to claim 10, characterized in that, The mesh generation device generates the mesh model using a neural network that outputs the mesh model based on input data representing the cutting area determined by the machining area determination unit.

12. The cutting system according to claim 10 or 11, characterized in that, It also has an additional processing device that manufactures the shape by adding material. The measuring device measures the shape of the shaped object, thereby determining the cutting area where the cutting is performed. The cutting processing device manufactures the processed article by cutting the shaped article.

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