• Title/Summary/Keyword: Gas metal arc welding(GMAW)

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A Study on On-Line Quality Monitoring Using Arc Light in Gas Metal Arc Welding (GMAW에서 아크 빛을 이용한 실시간 용접품질 모니터링에 관한 연구)

  • 조택동;양상민
    • Journal of Welding and Joining
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    • v.18 no.4
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    • pp.82-86
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    • 2000
  • Gas metal arc welding(GMAW) is regarded as one of the best candidate for welding automation in industrial joining application. It is important to monitor the weld quality for the high performance weld automation. In GMAW, weld quality is closely related to arc stability especially. In this paper, arc light signal is measured and spectrum analyzed to the detect the variation of the weld quality. The FFT of the signal showed that the amplitude variance of FFT power spectrum was very large in poor weld process such as the decrease of weld bead width and height. The results show that it is possible to detect the weld defect position in weld process.

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Dynamic behavior of GMA considering metal transfer (금속이행을 고려한 GMA 용접 시스템의 동특성 해석)

  • 박세홍;김면희;강세령;최상균;이상룡
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2002.05a
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    • pp.565-568
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    • 2002
  • Welding variables and conditions in gas metal arc welding (GMAW) effect on the weld quality and productivity, extensive research efforts have been made to analyze the welding variables and conditions. In this study dynamic behavior of GMAW system is investigated using the characteristic equations of the power supply, wire and welding arc. Characteristic equation of wire is modified to include the effect of droplets attached at the electrode tip. The dynamic characteristics of arc length, current, voltage with respect to the step, ramp inputs of CTWD was simulated, seam tracking procedure using arc sensor was simulated with variable V-Groove geometries and weaving frequencies. From results of simulation, some predictions about dynamic characteristics of GMAW and welding process are available. The proposed simulator and results appear to be utilized to determine the proper welding conditions, to be improved by considering power supply dynamic characteristics.

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The Analysis of Characteristics of GMAW using Sound Signal (음향 신호 분석에 의한 GMAW의 특성분석)

  • 조택동;양상민;양성빈
    • Proceedings of the KWS Conference
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    • 2002.05a
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    • pp.65-67
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    • 2002
  • The gas metal arc welding(GMAW) is regarded as one of the best candidate for welding automation in industrial joining application. It is important to monitor the weld quality for the high performance of weld automation. The measured analog signal is frequency analyzed by digital signal process method. In order to observe the welding phenomena and control welding condition, arc light, voltage, and current are measured at the same time. They are analyzed and compared with arc sound. for these experiments, a power source of constant voltage characteristics was used in the pure metal transfer mode.

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Development of Digital Gas Metal Arc Welding System and Welding Current Control Using Self-tuning Fuzzy PID

  • Doan, Phuc Thinh;Pratama, Pandu Sandi;Kim, Suk-Yoel;Kim, Hak-Kyeong;Yeun, Hwang-Yeong;Byun, Gi-Sig;Kim, Sang-Bong
    • Journal of Ocean Engineering and Technology
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    • v.25 no.6
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    • pp.1-8
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    • 2011
  • This paper describes a new method for a digital gas metal arc welding (GMAW) system. The GMAW system is an arc welding process that incorporates the GMAW power source (PS-GMAW) with a wire feed unit (WFU). The PS-GMAW requires an electric power of constant voltage. A constant magnitude is maintained for the arc current by controlling the wire-feed speed of the WFU. A mathematical model is derived, and a self-tuning fuzzy proportional-integral-derivative (PID) controller is designed and applied to control the welding current. The electrode wire feeding mechanism with this controller is driven by a DC motor, which can compensate for both the molten part of the electrode and undesirable fluctuations in the arc length during the welding process. By accurately maintaining the output welding current and welding voltage at constant values during the welding process, excellent welding results can be obtained. Simulation and experimental results are shown to prove the effectiveness of the proposed controller.

A Study on the Calculating Method of the Heat Input Efficiency in Arcspot Welding (아크 스폿 용접의 입열효율 계산 방법에 관한 연구)

  • Jang, Kyoung-Bok;Cho, Sang-Myoung
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.27 no.7
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    • pp.1065-1070
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    • 2003
  • In arc spot welding process, the arc is not moving and heat input is concentrated in one spot so that the heat input efficiency of arc is higher than that of GMAW. In other words, the heat input efficiency of arc change during weld time because arc start is done in spot and weld metal is filled. Therefore, the heat input model of arc spot welding should be different from that of general GMAW. In present study, the calculating model of heat input efficiency in arc spot welding was suggested by temperature monitoring near spot in arc spot welding of copper plate. The result showed that the heat input efficiency of arc was changed three times during weld time. The accuracy of calculating method of heat input efficiency was verified by heat transfer analysis of arc spot welding process using finite element method.

A study on the welding current and voltage signal processing method for the quality evaluation of robotic GMAW (GMAW 품질분석을 위한 신호처리 방법에 관한 연구)

  • Hong, Woo Heon;Ryu, Jeong Tak
    • Journal of Korea Society of Industrial Information Systems
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    • v.19 no.6
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    • pp.25-31
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    • 2014
  • Gas metal arc welding (GMAW) is currently the most widely used arc welding processes in the industry because of its high metal deposition rate, flexibility and low cost. It is attractive for high-productivity manufacturing applications and is well suited to automatic or robotic welding. Welding voltage and current have a significant impact on the weld bead. However, welding voltage and current are changed variously according to welding condition and user environment, and prediction is impossible. To determine the welding conditions, the welding current and voltage are applied to the appropriate data analysis techniques. In this paper, we used the moving average filter to the welding voltage and current data, and normal and abnormal welding waves were distinguished.

Dynamic Characteristics of Short Circuit in Pulse Gas Metal Arc Welding of Aluminum

  • Praveen, P;Kang, M.J.;Prasad, Yarlagadda K.D.V.;Kang, B.Y.
    • Proceedings of the KWS Conference
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    • 2005.06a
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    • pp.317-320
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    • 2005
  • In this paper, dynamic behaviour of short circuit occurring in Pulse Gas Metal Arc Welding (GMAW-P) is investigated Welding experiments with different values of pulsing parameters, high speed camera pictures and welding signals such as current and voltage were acquired to identify short circuit conditions in GMAW-P.

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A Study on Dynamic Characteristics of Welding Current and Arc Length At GMAW (GMA용접에서 용접전류와 아크 길이의 동특성에 관한 연구)

  • Lee, Tae-Young
    • Journal of the Korean Society of Industry Convergence
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    • v.14 no.1
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    • pp.15-21
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    • 2011
  • Welding variables and conditions in gas metal arc welding (GMAW) effect on the quality and productivity of the weld, extensive research efforts have been made to analyze the effect of the welding variables and conditions. In this study dynamic behavior of GMAW system is investigated using the characteristics of the power supply, wire and welding arc. Characteristic equation of wire is modified to include the effect of droplets attached at the electrode tip. The dynamic characteristics of arc length, current, voltage with respect to the step, ramp inputs of CTWD was simulated. From results of simulation, some predictions about dynamic characteristics of GMAW and welding process are available. The proposed simulator and results appear to be utilized to determine the proper welding conditions, to be improved by considering power supply dynamic characteristics.

A Study on Dynamic Characteristics of Welding voltage and Welding Current At GMAW (GMA 용접에서 전압과 전류의 동특성에 관한 연구)

  • Kim, Myun-Hee;Choi, Young-Geun;Lee, Moon-Hwan
    • Journal of the Korean Society of Industry Convergence
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    • v.4 no.2
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    • pp.207-213
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    • 2001
  • Welding variables and condition in gas metal arc welding (GMAW) effect on the weld quality and productivity, extensive research efforts have been made to analyze the welding variables and conditions. In this study dynamic behavior of GMAW system is investigated using the chararcteristic equations of the power supply. wire and welding arc. Characteristic equation of wire is modified to include the effect of droplets attached at the electrode tip. The dynamic characteristics of arc length, current, voltage with respect to the step, ramp inputs of CTWD was simulated. From results of simulation, some predictions about dynamic characteristics of GMAW and welding process are available. The proposed simulator and results appear to be utilized to determine the proper welding conditions, to be improved by considering power supply dynamic characteristics.

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Development of Inference Algorithm for Bead Geometry in GMAW using Neuro-Fuzzy (Neuro-Fuzzy를 이용한 GMA 용접의 비드형상 추론 알고리즘 개발)

  • 김면희;이종혁;이태영;이상룡
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2002.05a
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    • pp.608-611
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    • 2002
  • In GMAW(Gas Metal Arc Welding) process, bead geometry (penetration, bead width and height) is a criterion to estimate welding quality. Bead geometry is affected by welding current, arc voltage and travel speed, shielding gas, CTWB (contact- tip to workpiece distance) and so on. In this paper, welding process variables were selected as welding current, arc voltage and travel speed. And bead geometry was reasoned from the chosen welding process variables using negro-fuzzy algorithm. Neural networks was applied to design FL(fuzzy logic). The parameters of input membership functions and those of consequence functions in FL were tuned through the method of learning by backpropagation algorithm. Bead geometry could be reasoned from welding current, arc voltage, travel speed on FL using the results learned by neural networks.

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