WO2023027068A1 - Procédé d'inspection de soudure, système d'inspection de soudure et programme d'inspection de soudure - Google Patents

Procédé d'inspection de soudure, système d'inspection de soudure et programme d'inspection de soudure Download PDF

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Publication number
WO2023027068A1
WO2023027068A1 PCT/JP2022/031714 JP2022031714W WO2023027068A1 WO 2023027068 A1 WO2023027068 A1 WO 2023027068A1 JP 2022031714 W JP2022031714 W JP 2022031714W WO 2023027068 A1 WO2023027068 A1 WO 2023027068A1
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Prior art keywords
weld
welding
data
shape
point cloud
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PCT/JP2022/031714
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English (en)
Japanese (ja)
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弘隆 村松
ニック フォール
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リンクウィズ株式会社
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Publication of WO2023027068A1 publication Critical patent/WO2023027068A1/fr

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
    • B23K31/00—Processes relevant to this subclass, specially adapted for particular articles or purposes, but not covered by only one of the preceding main groups
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
    • G01B21/18—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring depth
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
    • G01B21/20—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring contours or curvatures, e.g. determining profile

Definitions

  • the present invention relates to a welding inspection technique for inspecting a welded portion of a welded target member.
  • Patent Document 1 discloses a technique for inspecting the weld shape by acquiring point cloud data representing the three-dimensional shape of the weld bead using imaging means. It is
  • the present invention has been made in view of such a background, and an object thereof is to provide a welding inspection device with improved accuracy in judging the quality of weld beads.
  • the main invention of the present invention for solving the above problems is a welding inspection system for inspecting the shape of a welded portion of an object to be measured, wherein the shape of the object to be measured is measured in a predetermined measurement area to obtain shape data.
  • a shape data acquisition unit that acquires welded portion data based on the acquired shape data; an area setting unit that divides and sets the welded portion into a plurality of areas;
  • a welding evaluation unit that performs welding evaluation for each area based on criteria set individually for each area of It is a welding inspection device characterized by the following.
  • FIG. 1 is a diagram showing an overall configuration example of a welding inspection system 100 of Embodiment 1.
  • FIG. 2 is a diagram showing how the welding inspection system 100 of Embodiment 1 is used to inspect a welded portion of an object to be inspected.
  • 2 is a diagram showing a hardware configuration example of the terminal 1 according to the first embodiment;
  • FIG. 2 is a diagram showing a functional configuration example of the terminal 1 according to the first embodiment;
  • FIG. FIG. 5 is a diagram showing an example of a flowchart of a welding inspection method according to the first embodiment;
  • 3 is a diagram showing an example of 3D point cloud data acquired by a 3D point cloud data acquisition unit 101 according to Embodiment 1.
  • FIG. 4 is a diagram showing an example of a reference plane 60 according to Embodiment 1.
  • FIG. FIG. 4 is a diagram showing an example of a method for extracting weld point cloud data from three-dimensional point cloud data according to the first embodiment
  • 6 is a diagram showing an example of weld point cloud data 70 acquired by a weld point cloud data acquiring unit according to the first embodiment
  • FIG. FIG. 7 is a diagram showing an example of a method of setting grid intersections set on a reference plane 60 according to the first embodiment
  • FIG. 10 is a diagram showing an example of selecting points corresponding to a plurality of grid intersection points from the welded portion point group data by the approximate surface generation unit according to the second embodiment
  • FIG. 10 is a diagram showing an example of data of a plurality of points corresponding to each grid intersection selected by the approximate surface generation unit according to the second embodiment
  • FIG. 11 is a diagram showing an example of mesh (approximate surface) generation by the approximate surface generation unit 103 according to the second embodiment.
  • FIG. 10 is a diagram showing an example of a method of extracting point cloud data separated by a predetermined distance or more from a mesh (approximate surface) according to the second embodiment;
  • FIG. 10 is a diagram showing an example of weld point cloud data 80 extracted from the weld point cloud data according to the second embodiment;
  • FIG. 9 is a diagram showing an example of a result of setting an area on a plane including welded portion point cloud data 80 by an area dividing unit according to the second embodiment;
  • FIG. 10 is a diagram showing an example of a method for dividing a plane area by an area dividing unit according to the second embodiment;
  • FIG. 10 is a diagram showing an example of a method for determining defective welding in each divided area according to the second embodiment;
  • the present invention has, for example, the following configurations.
  • a welding inspection system for inspecting the shape of a welded portion of an object to be measured, a shape data acquisition unit that acquires shape data by measuring the shape of the object to be measured in a predetermined measurement area; a weld data acquisition unit that acquires weld data based on the acquired shape data; an area setting unit that divides and sets the welded portion into a plurality of areas; a welding evaluation unit that performs welding evaluation for each area based on criteria individually set for each of the plurality of set areas;
  • a welding inspection system comprising: [Item 2] In the welding inspection system described in the item, The weld data acquired by the weld data acquisition unit includes information indicating the depth of the weld, The welding inspection system, wherein the welding evaluation unit performs the welding evaluation based on a depth determination threshold set for each of the plurality of areas.
  • the welding evaluation unit determines whether or not there is a portion having a depth exceeding the determination threshold in each of the plurality of areas, A weld inspection system characterized in that a weld is evaluated as defective if there is a portion with a depth exceeding .
  • the shape data acquisition unit acquires shape data of the object to be measured as three-dimensional point cloud data, The weld data acquisition unit generates an approximate plane based on a part of the point group selected from the three-dimensional point cloud data, and the perpendicular distance between the point group of the three-dimensional point cloud data and the approximate plane is predetermined.
  • a welding inspection system characterized by acquiring a point cloud exceeding a value as shape data of a weld.
  • the weld data acquisition unit generates a mesh composed of a plurality of triangles as an approximate surface using an approximate curve generated based on a partial point group selected from the three-dimensional point cloud data.
  • Weld inspection system characterized by: [Item 6] In the welding inspection system according to item 4 or item 5, The weld shape data acquisition unit sets a plurality of representative points on a plane of a reference plane defined based on coordinate information input by a user or pre-recorded coordinate information, and sets the plurality of representative points.
  • a welding inspection system characterized by selecting corresponding points closest to each other from the three-dimensional point group data and generating an approximate curve based on the plurality of selected corresponding points.
  • a welding inspection method for inspecting the shape of a welded portion of an object to be measured obtaining shape data by measuring the shape of the object to be measured in a predetermined measurement area; a step of acquiring data of the weld based on the acquired shape data; setting the weld zone by dividing it into a plurality of areas; a step of performing welding evaluation for each area based on criteria individually set for each of the plurality of set areas;
  • a welding inspection method comprising: [Item 8] A welding inspection program for causing a computer to execute a welding inspection method for inspecting the shape of a welded portion of a measurement object, The welding inspection program includes, as the welding inspection method, A welding inspection method for inspecting the shape of a welded portion of an object to be measured, obtaining shape data by measuring the shape of the object to be measured in a predetermined measurement area
  • FIG. 1 is a diagram showing an example of a welding inspection system 100 of this embodiment.
  • the welding inspection system 100 of this embodiment has a terminal 1 , a working robot 2 and a controller 3 .
  • the working robot 2 has at least an arm 21 and a sensor 22 .
  • the terminal 1, the controller 3, and the working robot 2 are connected by wire or wirelessly so as to be able to communicate with each other.
  • FIG. 2 is a diagram showing how the welding inspection system 100 is used to inspect a welded portion of an object welded by laser welding or the like.
  • the sensor 22 provided on the arm 21 of the working robot 2 acquires point cloud data of the surface shape of a predetermined area including the welded portion 401 of the inspection object 4 .
  • FIG. 3 is a diagram showing the hardware configuration of the terminal 1.
  • the terminal 1 may be, for example, a general-purpose computer such as a personal computer, or may be logically realized by cloud computing. Note that the illustrated configuration is an example, and other configurations may be employed. For example, some functions provided in the processor 10 of the terminal 1 may be executed by an external server or another terminal.
  • the terminal 1 includes at least a processor 10 , a memory 11 , a storage 12 , a transmission/reception section 13 , an input/output section 14 and the like, which are electrically connected to each other through a bus 15 .
  • the processor 10 is an arithmetic device that controls the overall operation of the terminal 1, controls at least transmission and reception of data to and from the working robot 2, executes applications, and performs information processing necessary for authentication processing.
  • the processor 10 is a CPU (Central Processing Unit) and/or a GPU (Graphics Processing Unit), and executes programs for this system stored in the storage 12 and developed in the memory 11 to perform each information processing. .
  • the memory 11 includes a main memory composed of a volatile memory device such as a DRAM (Dynamic Random Access Memory), and an auxiliary memory composed of a non-volatile memory device such as a flash memory or a HDD (Hard Disc Drive). .
  • the memory 11 is used as a work area or the like for the processor 10, and stores a BIOS (Basic Input/Output System) executed when the terminal 1 is started, various setting information, and the like.
  • BIOS Basic Input/Output System
  • the storage 12 stores various programs such as application programs.
  • a database storing data used for each process may be constructed in the storage 12 .
  • the transmitting/receiving unit 13 connects the terminal 1 to at least the work robot 2, and transmits/receives data according to instructions from the processor.
  • the transmitting/receiving unit 13 is configured by wire or wireless, and in the case of wireless, for example, it may be configured by a short-range communication interface such as WiFi, Bluetooth (registered trademark), and BLE (Bluetooth Low Energy). .
  • the input/output unit 14 is configured by an information output device (eg, a display) and an information input device (eg, a keyboard and a mouse), and when configured by a smartphone or a tablet terminal. is composed of information input/output devices such as a touch panel.
  • a bus 15 is commonly connected to the above elements and transmits, for example, address signals, data signals and various control signals.
  • the working robot 2 has an arm 21 and a sensor 22.
  • the illustrated configuration is an example, and is not limited to this configuration.
  • the movement of the arm 21 is controlled by the terminal 1 based on the three-dimensional robot coordinate system.
  • the arm 21 may further include a controller 3 connected to the work robot 2 by wire or wirelessly, thereby controlling its operation.
  • the sensor 22 performs sensing of the inspection object 4 based on the three-dimensional sensor coordinate system.
  • the sensor 22 is, for example, a laser sensor that operates as a three-dimensional scanner, and obtains three-dimensional point cloud data 50 of the inspection object 4 by sensing.
  • the three-dimensional model data 50 is, for example, three-dimensional point cloud data as shown in FIG. 6, each point data has coordinate information of the sensor coordinate system, and the shape of the inspection object is grasped by the point cloud. becomes possible.
  • the sensor 22 is not limited to a laser sensor, and may be, for example, an image sensor using a stereo system or the like, or may be a sensor independent of the working robot. Anything that can acquire coordinate information can be used.
  • a configuration using three-dimensional point group data as the three-dimensional model data 50 will be described below as an example.
  • a predetermined calibration is performed before work, the robot coordinate system and the sensor coordinate system are associated with each other, and the user designates the position (coordinates) based on the sensor coordinate system.
  • the configuration may be such that the operation is controlled based on the position.
  • FIG. 4 is a block diagram illustrating functions implemented in the terminal 1.
  • the processor 10 of the terminal 1 includes a three-dimensional point cloud data acquisition unit (three-dimensional model data acquisition unit) 101, a reference plane setting unit 102, an approximate surface generation unit 103, and a weld point cloud data extraction unit. 104 , an area dividing section 105 and a welding evaluation section 106 .
  • the storage 12 of the terminal 1 also has a three-dimensional point cloud data storage unit (three-dimensional model data storage unit) 121 , a weld point cloud data storage unit 122 , and a welding evaluation result storage unit 123 .
  • the three-dimensional point cloud data acquisition unit 101 controls, for example, the working robot 2 according to instructions from the input/output unit 14 of the terminal 1, operates the arm 21 and the sensor 22, and obtains three-dimensional point cloud data of the inspection object 4. Get 40.
  • the operations of the arm 21 and the sensor 22 are set in advance so that the three-dimensional point cloud data of the area including the welded portion 401 of the inspection object 4 can be obtained.
  • the acquired 3D point cloud data is, for example, 3D coordinate information data based on the sensor coordinate system, and is stored in the 3D point cloud data storage unit 121 .
  • FIG. 6 is a diagram showing an example of the 3D point cloud data 40 acquired by the 3D point cloud data acquisition unit 101.
  • the three-dimensional point cloud data is three-dimensional point cloud data that is shape data of a region including the welded portion 401 of the inspection target 4.
  • the three-dimensional point cloud data is shape data of a region including the welded portion 401 of the inspection target 4.
  • the weld point cloud data acquisition unit 102 first obtains a reference for covering the weld area based on the position coordinate information indicating the weld area input by the user through the input/output unit 14 of the terminal 1 or recorded in the system in advance.
  • a plane 60 is set.
  • FIG. 7 is a diagram showing an example of a reference plane. As shown in FIG. 7, the reference plane 60 is input or preset by the user to be, for example, a plane that covers the area of the weld and is substantially parallel to the plane of the weld. Also, the area of the reference plane 60 is set by three or more points.
  • FIG. 8 is a diagram showing an example of extracting weld point cloud data 51 from three-dimensional point cloud data 50 based on the reference plane.
  • a point cloud existing in a position perpendicular to the reference plane 50 and overlapping with the reference plane is extracted as weld point cloud data 51, and the extracted weld point cloud data 51 is used as welding point cloud data.
  • the data is stored in the point cloud data storage unit 122 .
  • FIG. 9 is a diagram showing an example of the extracted weld point cloud data 51.
  • the extracted welded portion point cloud data 51 is the point cloud data of the area centering on the welded portion 401 .
  • the approximate plane generation unit 103 first sets grid intersection points 61 on the reference plane 60 .
  • FIG. 10 shows an example of a method of setting the grid intersection points on the reference plane 60 .
  • grid lines are defined at positions that vertically and horizontally divide the reference plane 60 into four equal parts, and 25 grid intersections, which are the intersections of the grid lines, are set.
  • the interval between grid lines does not necessarily have to be an interval that divides the reference plane into four equal parts, and can be set arbitrarily.
  • the approximate surface generation unit 103 selects points corresponding to a plurality of grid intersection points from the weld point cloud data.
  • FIG. 11 shows an example of selecting points corresponding to a plurality of grid intersection points from the weld point cloud data.
  • the point closest to each grid intersection point in the three-dimensional space is determined as the weld point.
  • Select from group data FIG. 12 shows an example of data of a plurality of points corresponding to grid intersection points obtained by the processing. Since the plurality of points shown in FIG. 12 are 25 point data selected from the weld point cloud data, they indicate the three-dimensional coordinates of the surface of the inspection object 4 .
  • FIG. 13 shows two-dimensionally an example of the approximate surface generation unit 103 generating an approximate surface from a mesh composed of a plurality of triangles.
  • an approximation curve is generated based on a plurality of point data corresponding to the grid intersection points selected by the above-described processing, and a mesh (approximation surface) composed of a plurality of triangles is generated by this approximation curve. do. It can be considered that the approximate surface generated in this manner approximates the surface shape of the original disk before the inspection object 4 is welded.
  • the weld point cloud data extraction unit 104 extracts point cloud data separated by a predetermined distance or more from the generated mesh (approximate surface).
  • FIG. 14 shows an example of a method of extracting point cloud data separated from a mesh (approximate surface) by a predetermined distance or more.
  • the weld point cloud data extraction unit 104 calculates the length of the vector orthogonal to the triangles forming the mesh for each point of the weld point cloud data, and calculates the distance from the mesh. If there are vectors orthogonal to multiple triangles, select the vector with the shortest distance. Then, points whose distance from the mesh is greater than a distance threshold input by the user or set in advance by the input/output unit 14 are extracted as the welded portion point cloud data 80 .
  • FIG. 15 is a diagram showing an example of weld point cloud data 80 extracted from the weld point cloud data based on the above process.
  • the point group separated from the mesh by a predetermined distance or more is the point group from the surface of the master disk of the inspection object 4. It can be regarded as data of a point group separated by a predetermined distance or more.
  • the area dividing unit 105 first sets an area on a plane containing the extracted weld point cloud data 80 . For example, based on the first and second points selected by the user via the terminal 1 a vector of the longitudinal direction of the planar area is defined, and based on the third selected point a short vector perpendicular to said longitudinal direction is defined. A vector of edge directions is defined.
  • the positions of both ends of the planar area are set based on the coordinates of the located points.
  • FIG. 16 is a diagram showing an example of a result of setting an area on a plane containing the weld point cloud data 80. As shown in FIG. As shown in FIG. 16 , the plane area 62 is set so that there is almost no marginal area outside the weld point cloud data 80 .
  • the area dividing unit 105 divides the set planar area into a plurality of areas.
  • FIG. 17 shows an example of a method of dividing a planar area. As shown in FIG. 17, for example, the planar area is divided into four areas by connecting the midpoints of the sides in the longitudinal direction and the lateral direction. Furthermore, the four divided areas are defined as three areas: the start area containing the welding start position, the end area containing the welding end position, and the main area containing the welded part between the welding start position and the end position. be done. For example, the area containing or closest to the first selected point by the user by terminal 1 is the start area, the area containing or closest to the second selected point is the end area, and the remaining two areas are merged. Each area after division can be defined as a main area.
  • the welding evaluation unit 106 sets different criteria for determining defective welding for each of the three defined areas, and determines defective welding based on the criteria.
  • FIG. 18 is a diagram showing an example of a method of determining defective welding in each divided area. As an example of welding defect determination, for example, as shown in FIG. are extracted for each area. A different threshold value for failure determination is provided for each of the three defined areas, and it is determined whether or not the deepest point of the concave portion in each area exceeds the threshold value for failure determination of the area. If there is a point in the area with a depth exceeding the failure determination threshold value, it is possible to determine that the weld is defective. Information on the evaluation results evaluated by welding evaluation unit 106 is stored in welding evaluation result storage unit 123 .
  • FIG. 5 is an example of a flowchart of a welding inspection method in the welding inspection system 100 of the first embodiment.
  • the user inputs a command to inspect the welded portion 401 of the inspection object 4 from the terminal 1, and operates the arm 21 and the sensor 22 to obtain the three-dimensional point cloud data acquisition unit 101, for example, FIG. acquires the reference three-dimensional point cloud data 50 of the inspection object 4 positioned on the workbench as shown in (step 101).
  • the weld point cloud data acquisition unit 102 sets a reference plane based on the information of a plurality of point coordinates input by the user through the terminal or information pre-recorded in the welding inspection system. For example, as shown in FIG. 7, the reference plane is set at a predetermined orientation and position that covers the area of the weld and is substantially parallel to the surface of the weld. Also, the area of the reference plane 60 may be set by three or more points. (Step 102).
  • the weld point cloud data acquisition unit 102 acquires the weld point cloud data existing within the area set by the reference plane 60 from the three-dimensional point cloud data 50 (step 103).
  • the point cloud existing in the vertical projection area of the reference plane 60 is obtained from the three-dimensional point cloud data 50, thereby extracting the weld point cloud data 51.
  • the point group to be extracted is not limited to those present in the vertical projection area strictly perpendicular to the reference plane 60 , and a point group present at a position substantially perpendicular to the reference plane 60 may be extracted.
  • the approximate surface generation unit 103 sets grid lines in a grid pattern vertically and horizontally on the reference plane 60 at predetermined intervals, and sets intersection points of the grid lines as grid intersection points (step 104).
  • grid lines are set at positions where the vertical and horizontal lengths of the reference plane 60 are 25%, and each intersection point is set as the grid intersection point 61 .
  • the approximate surface generation unit 103 selects corresponding points 52 with the closest three-dimensional coordinates for each grid intersection from the weld point cloud data (step 105).
  • FIG. 11 shows two-dimensionally the process of selecting this corresponding point 52 .
  • the approximate surface generation unit 103 generates an approximate curve based on the corresponding points 52, and creates a mesh (approximate surface) by the approximate curve (step 106).
  • FIG. 13 shows an image diagram of generating an approximate curve based on the corresponding points 52. As shown in FIG.
  • the weld point cloud data extracting unit 104 calculates the distance from each point of the weld point cloud data to the mesh (approximate surface), and extracts the points separated from the mesh by a predetermined distance or more into the weld point cloud data. 80 (step 107).
  • the mesh (approximate surface) is a surface approximating the master surface of the inspection object 4 before welding
  • the weld point cloud data 80 is projected from the master surface of the inspection object 4 before welding. It is a point cloud of a convex part and a concave part that are depressed.
  • the area dividing unit 105 sets a rectangular planar area 62 that includes the weld point cloud data 80 and has a small surplus area on the outside.
  • the plane area 62 is divided into four areas by vertically and horizontally dividing the plane area 62 into two at the center position, and the point including or closest to the point first selected by the user with the terminal 1 is divided into four areas.
  • the welding evaluation unit 106 measures the depth distance of the recess by calculating the distance of each point from the mesh 70 in each area, and outputs the maximum value of the depth of the recess for each area (step 108 ).
  • the maximum value of the recess depth measured for each area is compared with different determination thresholds set in advance for each area, so that the depth of the recess is determined by the determination threshold in at least one of the areas. It is also possible to determine that the weld is bad if there are points (portions) that are deeper than the value. Specifically, if there is a pit (a small recessed hole) that occurs on the surface of the weld bead, it can be determined that the weld is defective. Degradation can be detected.
  • the welding head tends to stay in the same position for a longer time in order to start welding in the welding start area, so the depth of the recess becomes deeper.
  • the depth of the concave portion is relatively shallow because the welding head moves stably at a constant speed.
  • convex portions to be formed in the end area.
  • the maximum depth of the concave portion can be measured for each area of the weld bead, and normality/abnormality can be determined for each area. It is possible to improve the accuracy of the welding failure determination compared to determining the welding failure using the determination threshold value.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Length Measuring Devices By Optical Means (AREA)
  • Length Measuring Devices With Unspecified Measuring Means (AREA)

Abstract

[Problème] La présente invention aborde le problème visant à améliorer la précision de l'inspection de qualité de cordons de soudure. [Solution] Ce système d'inspection de soudure est destiné à inspecter la forme d'une partie soudée d'un objet à mesurer, et est caractérisé en ce qu'il comprend : une unité d'acquisition de données de forme qui acquiert des données de forme par mesure de la forme de l'objet à mesurer dans une région de mesure prescrite ; une unité d'acquisition de données de partie soudée qui acquiert des données d'une partie soudée sur la base des données de forme acquises ; une unité de définition de zone qui définit une pluralité de zones par division de la partie soudée ; et une unité d'évaluation de soudure qui, sur la base de critères de détermination définis pour chacune des zones qui ont été définies, effectue une évaluation de soudure dans les zones respectives.
PCT/JP2022/031714 2021-08-24 2022-08-23 Procédé d'inspection de soudure, système d'inspection de soudure et programme d'inspection de soudure WO2023027068A1 (fr)

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JP2021-136481 2021-08-24

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Cited By (1)

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CN116673572A (zh) * 2023-07-31 2023-09-01 天津悦华阀门科技有限公司 一种基于人工智能的机械焊接数据管理分析系统

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Publication number Priority date Publication date Assignee Title
JP2000158134A (ja) * 1998-11-24 2000-06-13 Chuo Motor Wheel Co Ltd アーク溶接安定性判定方法及び装置
JP2008246536A (ja) * 2007-03-30 2008-10-16 Ihi Corp 溶接状況解析装置及び方法
JP2012037487A (ja) * 2010-08-11 2012-02-23 Koatec Kk 形状検査装置及び形状検査方法
JP2014014856A (ja) * 2012-07-11 2014-01-30 Suzuki Motor Corp 画像処理方法及び画像処理システム

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2000158134A (ja) * 1998-11-24 2000-06-13 Chuo Motor Wheel Co Ltd アーク溶接安定性判定方法及び装置
JP2008246536A (ja) * 2007-03-30 2008-10-16 Ihi Corp 溶接状況解析装置及び方法
JP2012037487A (ja) * 2010-08-11 2012-02-23 Koatec Kk 形状検査装置及び形状検査方法
JP2014014856A (ja) * 2012-07-11 2014-01-30 Suzuki Motor Corp 画像処理方法及び画像処理システム

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116673572A (zh) * 2023-07-31 2023-09-01 天津悦华阀门科技有限公司 一种基于人工智能的机械焊接数据管理分析系统
CN116673572B (zh) * 2023-07-31 2023-09-26 天津悦华阀门科技有限公司 一种基于人工智能的机械焊接数据管理分析系统

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