• Title/Summary/Keyword: seam welding

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Study of Intelligent Vision Sensor for the Robotic Laser Welding

  • Kim, Chang-Hyun;Choi, Tae-Yong;Lee, Ju-Jang;Suh, Jeong;Park, Kyoung-Taik;Kang, Hee-Shin
    • Journal of the Korean Society of Industry Convergence
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    • v.22 no.4
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    • pp.447-457
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    • 2019
  • The intelligent sensory system is required to ensure the accurate welding performance. This paper describes the development of an intelligent vision sensor for the robotic laser welding. The sensor system includes a PC based vision camera and a stripe-type laser diode. A set of robust image processing algorithms are implemented. The laser-stripe sensor can measure the profile of the welding object and obtain the seam line. Moreover, the working distance of the sensor can be changed and other configuration is adjusted accordingly. The robot, the seam tracking system, and CW Nd:YAG laser are used for the laser welding robot system. The simple and efficient control scheme of the whole system is also presented. The profile measurement and the seam tracking experiments were carried out to validate the operation of the system.

Development of a High Speed Rotating Arc Sensor System for Tracking Complicate Curved Fillet Welding Lines

  • Lee, Gun-You;Oh, Myung-Suck;Kim, Sang-Bong
    • International Journal of Precision Engineering and Manufacturing
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    • v.4 no.6
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    • pp.20-28
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    • 2003
  • This paper presents development of a high speed rotating arc sensor system using a microprocessor based controller with tracking function for a complicate curved fillet welding line, The welding tip connected to the torch body is eccentrically positioned from the centerline of the torch, The area during one rotating cycle is divided into 4 regions of front, rear, right and left in welding direction of the torch tip to determine the horizontal deviation between the welding seam and the torch position. The average value at each region is calculated using the regional current values and a low pass filter incorporated with the moving average method is implemented. The effectiveness of the developed system is proven through the experimental results for several kinds of complicate curved fillet welding lines.

Development of Mobile Robot for Welding of Lattice Type - Mobile Speed Control and Seam Tracking Control - (격자형 용접 주행로봇의 개발 ( 제1보 : 주행제어 및 용접선 추적제어 ))

  • 감병오;전양배;강치정;주갑영;김상봉
    • Proceedings of the KWS Conference
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    • 2000.10a
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    • pp.34-36
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    • 2000
  • It is difficult to realize automation of welding of lattice type in shipbuilding and assembly processing of shipbuilding and steel structures. Usually, the welding parts of lattice type are welded manually. So there are limitations in continuous and stable quality controls and in increase in productivity because the welding quality depends on worker's skill. That is, automation in welding is necessary. This paper shows shows the development results of a moblie robot for welding of lattice type. Specially. algorithms for its mobile speed and seam tracking controls are introduced.

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The Multipass Joint Tracking System by Vision Sensor (비전센서를 이용한 다층 용접선 추적 시스템)

  • Lee, Jeong-Ick;Koh, Byung-Kab
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.16 no.5
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    • pp.14-23
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    • 2007
  • Welding fabrication invariantly involves three district sequential steps: preparation, actual process execution and post-weld inspection. One of the major problems in automating these steps and developing autonomous welding system is the lack of proper sensing strategies. Conventionally, machine vision is used in robotic arc welding only for the correction of pre-taught welding paths in single pass. However, in this paper, multipass tracking more than single pass tracking is performed by conventional seam tracking algorithm and developed one. And tracking performances of two algorithm are compared in multipass tracking. As the result, tracking performance in multi-pass welding shows superior conventional seam tracking algorithm to developed one.

Study on CAD/CAM Interfacing for Robot based Laser Welding (로봇 레이저용접을 위한 캐드캠 인터페이싱에 관한 연구)

  • Gang, Hui-Sin;Seo, Jeong;Kim, Jeong-O;Park, Gyeong-Taek;Jo, Taek-Dong
    • Proceedings of the KWS Conference
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    • 2007.11a
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    • pp.67-69
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    • 2007
  • Laser welding technology for automobile body is studied. Laser system, robot and seam tracking system are used for 3D laser welding system. The laser system is used 4kW Nd:YAG laser(HL4006D) of Trumpf and the robot system is used IRB6400R of ABB. The seam tracking system is SMRT-20LS of ServoRobot. The welding joints of steel plate are butt and lap joint. The 3 dimensional laser welding for non-linear pipe welding line is performed.

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Development of 3D Laser Welding Technology for Automobile body (자동차 차체 3차원 레이저 용접기술 개발)

  • Jeong, Byeong-Hun;Lee, Mun-Yong;Seo, Jeong;Gang, Hui-Sin
    • Proceedings of the KWS Conference
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    • 2005.06a
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    • pp.103-105
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    • 2005
  • Laser welding technology for automobile body is studied. laser system, robot and seam tracking system are used for 3D laser welding system The laser system is used 4kW Nd:YAG laser(HL4006D) of Trumpf and the robot system is used IRB6400R of ABB. The seam tracking system is SMRT-20LS of ServoRobot. The welding joints of steel plate are butt and lap joint. The 3-D welding for non-linear tailored blank is performed after experiments of bead on plate. Finally, the welding process for non-linear tailored blank is developed.

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Diagnosis for the Welding Condition of the CAL Process using Neuro-Fuzzy System (뉴로-퍼지 시스템을 이용한 CAL공정내 용접상태 진단)

  • 김경민;김이곤;박중조;송명현;정양희;배영철;최남섭
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.4 no.4
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    • pp.885-893
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    • 2000
  • The use of neural-fuzzy system to model mesh seam welding is described in this paper. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters affecting quality include the arc voltage, the welding current, torch travel speed and the pressure and so on. The relationship between the welding parameters and weld quality is not a direct one, and in addition, the effect of the weld parameter variables are not independent of the each other. The effectiveness of the proposed neuro-fuzzy algorithms is demonstrated by computer simulations.

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A Study on Automatic Seam Tracking using Vision Sensor (비전센서를 이용한 자동추적장치에 관한 연구)

  • 전진환;조택동;양상민
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1995.10a
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    • pp.1105-1109
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    • 1995
  • A CCD-camera, which is structured with vision system, was used to realize automatic seam-tracking system and 3-D information which is needed to generate torch path, was obtained by using laser-slip beam. To extract laser strip and obtain welding-specific point, Adaptive Hough-transformation was used. Although the basic Hough transformation takes too much time to process image on line, it has a tendency to be robust to the noises as like spatter. For that reson, it was complemented with Adaptive Hough transformation to have an on-line processing ability for scanning a welding-specific point. the dead zone,where the sensing of weld line is impossible, is eliminated by rotating the camera with its rotating axis centered at welding torch. The camera angle is controlled so as to get the minimum image data for the sensing of weld line, hence the image processing time is reduced. The fuzzy controller is adapted to control the camera angle.

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Study on the Seam Tracking by Using Fiber Sensor and X-Y Robot (Fiber Sensor와 X-Y Robot을 이용한 용접선 추적에 관한 연구)

  • 배철오;이성근;김윤식;안병원;박영산
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2000.10a
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    • pp.558-561
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    • 2000
  • There are many types of seam tracking methods actually used in industrial spot. Lately, Non-contact sensor technics are mostly used because non-contact sensor has more advantage than contact sensor in many parts. This paper also concerned about fiber sensor a kind of non-contact sensor. X-Y robot and fiber sensor scan the seam tracking to be weld. After scanning, X-Y robot moves the first working point of being scanned and welding starts automatically. It makes an experiment on some types of Seam tracking like straight line tracking, leaned line tracking and curved line tracking to confirm how well the fibers sensor tracks the seam pass to be weld. And the seam pass that had been tracked was welded by inverter CO2 welding machine.

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