• Title/Summary/Keyword: 용접 결함

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Effects of Painting on the Weldability in $CO_2$ Welding ($CO_2$ 용접시 Painting이 용접성에 미치는 영향)

  • 김창목
    • Journal of Welding and Joining
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    • v.2 no.2
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    • pp.22-28
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    • 1984
  • $CO_2$ 용접은 50년 중반경에 실용화되어 조선물량의 증가와 더불어 발전해 왔다. 당사(대우조선)에서는 81년 CO$_{2}$ 용접기를 도입한 이래 84년 초부터 $CO_2$ 용접법의 확대 보급을 목적으로, 페인트가 용접성에 미치는 영향을 연구하였다. 유기페인트와 무기페인트 등 페인트 종류를 달리했을 때 용접결함의 발생정도, 도막 두께를 달리했을 때 결함의 원인 중 가장 크게 영향을 미치는 용접결함의 발생 정도, 기타 용접조건에 따른 용접결함의 발생정도를 실험을 통하여 연구하였다. 연구 결과에 의하여 당사에서는 무기페인트의 사용이 권장되고 있다.

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Development of an Intelligent Ultrasonic Signature Classification Software for Discrimination of Flaws in Weldments (용접 결함 종류 판별을 위한 지능형 초음파 신호 분류 소프트웨어의 개발)

  • Kim, H.J.;Song, S.J.;Jeong, H.D.
    • Journal of the Korean Society for Nondestructive Testing
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    • v.17 no.4
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    • pp.248-261
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    • 1997
  • Ultrasonic pattern recognition is the most effective approach to the problem of discriminating types of flaws in weldments based on ultrasonic flaw signals. In spite of significant progress in the research on this methodology, it has not been widely used in many practical ultrasonic inspections of weldments in industry. Hence, for the convenient application of this approach in many practical situations, we develop an intelligent ultrasonic signature classification software which can discriminate types of flaws in weldments based on their ultrasonic signals using various tools in artificial intelligence such as neural networks. This software shows the excellent performance in an experimental problem where flaws in weldments are classified into two categories of cracks and non-cracks. This performance demonstrates the high possibility of this software as a practical tool for ultrasonic flaw classification in weldments.

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Adaption of Neural Network Algorithm for Pattern Recognition of Weld Flaws (용접결함 패턴인식을 위한 신경망 알고리즘 적용)

  • Kim, Chang-Hyun;Yu, Hong-Yeon;Hong, Sung-Hoon
    • The Journal of the Korea Contents Association
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    • v.7 no.1
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    • pp.65-72
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    • 2007
  • In this study, we used nondestructive test based on ultrasonic test as inspection method and compared backpropagation neural network(BPNN) with probabilistic neural network(PNN) as pattern recognition algorithm of weld flaws. For this purpose, variables are applied the same to two algorithms. Where, feature variables are zooming flaw signals of reflected whole signals from weld flaws in time domain. Through this process, we compared advantages/ disadvantages of two algorithms and confirmed application methods of two algorithms.

Development of Expert System for Diagnosis of Weld Defects (용접 결함 진단 전문가시스템의 개발)

  • 박주용
    • Journal of Advanced Marine Engineering and Technology
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    • v.20 no.1
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    • pp.13-23
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    • 1996
  • Weld defects degrade the strength and safety of astructure and are resulted from the various cases. The complexity of causal relation of weld defects requires an expert for the analysis of weld defects and the measures counter to them. An expert system has the intelligent functions such as the representation of knowledge and the inference. On this research, weld defect are systematically analysed and their causal model is developed. This information is saved to the knowledge base. The suitable inference algorithm for the diagnosis of weld defects is developed and realized with C++ programming.

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용접결함이 횡방향 맞대기 용접부의 정적강도특성에 미치는 영향에 관한 실험적 연구

  • 장동일;채원규;경갑수;홍성욱
    • Proceedings of the Korean Institute of Industrial Safety Conference
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    • pp.175-180
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    • 1999
  • 대부분의 강구조물에서 주부재를 연결하는 경우 강재중량의 감소를 도모하거나 구조물의 미관을 고려해서 맞대기 용접이음방법을 주로 적용하고 있다. 일반적으로 횡방향 맞대기 용접부에서 발생할 수 있는 용접결함의 예로써는 그림1∼그림 3에서 알 수 있는 바와 같이 용입부족, 용융불량 등과 같은 평면적 결함과 공동, 슬래그혼입 등과 같은 입체적 결함을 거론할 수 있다. (중략)

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Characterization of Acoustic Emission Signal for Welding Flaw and Stress Corrosion of SPPH Steels (SPPH강의 용접결함과 응력부식에 따른 음향 방출 신호의 특성)

  • Kim, Sung-Dai;Jung, Woo-Gwang;Lee, Jong-O;Jung, Yu-Jin
    • Journal of the Korean Society for Nondestructive Testing
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    • v.27 no.2
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    • pp.97-104
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    • 2007
  • An investigation has been made on the relationship between characteristics of Acoustic Emission (AE) signal in welding flaw and the stress corrosion defect in-service for the high pressure pipe steel. In order to tackle the problem of welding flaw in high pressure pipe, specimens were made by the aid of the application of both corrosion liquid usage and a quenching method after local heating. The amplitude of signal was $60{\sim}75\;dB$ in the territory which is suspected for defect, and the specimens which only have welding flaw showed gradients of 0.034, 0.034, 0.035. Moreover, there is a certain increase in gradient even though the differences are very slight. That is, corrosion specimens showed new gradients of 0.040, 0.039, 0.041 which put welding flaw and corrosion mechanism together. After pressurizing 3 minutes, AE signal has been detected from welding flaw easily in each part of the section. It is possible to predict the occurrence and also prevent the damage of stress corrosion crack which has characteristics of cleavage fracture.

A Study on the effect of welding wire diameter on the welding quality detection (용접 와이어 직경이 용접 상태 검출에 미치는 영향)

  • Ryu, Jeong Tak
    • Journal of the Korea Industrial Information Systems Research
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    • v.21 no.2
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    • pp.39-44
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    • 2016
  • Using the welding current and voltage signal processing, we have studied the influence that the diameter of the welding wire to the welding quality detection. For the experiments, We have analyzed the signal with respect to large and small artificially a gap between base materials than the welding wire. In this experiment, the 1.2 mm diameter of the welding wire was used, and distance between the welding base materials was respectively 1.0 mm and 2.0 mm. In the welding with a large defect than the diameter of the welding wire it was able to detect a change in the welding current and welding voltage. But it could not detect a change in the welding current and welding voltage in the welding has a small defect than the welding wire diameter.