• Title/Summary/Keyword: multifeature pattern recognition

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A Study on Weldability Estirmtion of Laser Welded Specimens by Vision Sensor (비전 센서를 이용한 레이져 용접물의 용접성 평가에 관한 연구)

  • 엄기원;이세헌;이정익
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1995.10a
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    • pp.1101-1104
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    • 1995
  • Through welding fabrication, user can feel an surficaial and capable unsatisfaction because of welded defects, Generally speaking, these are called weld defects. For checking these defects effectively without time loss effectively, weldability estimation system setup isan urgent thing for detecting whole specimen quality. In this study, by laser vision camera, catching a rawdata on welded specimen profiles, treating vision processing with these data, qualititative defects are estimated from getting these information at first. At the same time, for detecting quantitative defects, whole specimen weldability estimation is pursued by multifeature pattern recognition, which is a kind of fuzzy pattern recognition. For user friendly, by weldability estimation results are shown each profiles, final reports and visual graphics method, user can easily determined weldability. By applying these system to welding fabrication, these technologies are contribution to on-line weldability estimation.

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The Weldability Estimation for the Purpose of Real-Time Inspection and Control (실시간 검사 및 제어를 목적으로 한 용접성 평가)

  • Lee, Jeong-Ick
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.9 no.3
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    • pp.605-610
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    • 2008
  • Through welding fabrication, user can feel unsatisfaction of surface quality because of welded defects, Generally speaking, these are called weld defects. For checking these defects effectively without time loss effectively, weldability estimation system setup is an urgent thing for detecting whole specimen quality. In this study, by laser vision camera, catching a rawdata on welded specimen profiles, treating vision processing with these data, qualitative defects are estimated from getting these information at first. At the same time, for detecting quantitative defects, whole specimen weldability estimation is pursued by multifeature pattern recognition, which is a kind of fuzzy pattern recognition. For user friendly, by weldability estimation results are shown each profiles, final reports and visual graphics method, user can easily determined weldability. By applying these system to welding fabrication, these technologies are contribution to on-line weldability estimation.