• Proceedings of the KWS Conference
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• 2002.05a
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• pp.207-210
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• 2002

• Proceedings of the KWS Conference
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• 2007.11a
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• pp.319-321
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• 2007

• Journal of the Korean Society for Nondestructive Testing
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• v.15 no.2
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• pp.395-406
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• 1995

Classification of flaws in weldments from their ultrasonic scattering signals is very important in quantitative nondestructive evaluation. This problem is ideally suited to a modern ultrasonic pattern recognition technique. Here brief discussion on systematic approach to this methodology is presented including ultrasonic feature extraction, feature selection and classification. A stronger emphasis is placed on probabilistic neural networks as efficient classifiers for many practical classification problems. In an example probabilistic neural networks are applied to classify flaws in weldments into 3 classes such as cracks, porosity and slag inclusions. Probabilistic nets are shown to be able to exhibit high performance of other classifiers without any training time overhead. In addition, forward selection scheme for sensitive features is addressed to enhance network performance.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.1
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• pp.46-51
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• 2015

Stainless steel is a popular structural materials for liquid-hydrogen storage containers and piping components for transporting high-temperature fluids because of its superior material properties such as high strength and high corrosion resistance at elevated temperatures. In general, tungsten inert gas (TIG) arc welding is used for bonding stainless steel. However, it is often reported that the thermal fatigue cracks or initial defects in stainless steel after welding decreases the reliability of the material. The objective of this paper is to clarify the characteristics of ultrasonic guided wave propagation in relation to a change in the initial crack length in the welding zone of stainless steel. For this purpose, three specimens with different artificial defects of 5 mm, 10 mm, and 20 mm in stainless steel welds were prepared. By considering the thickness of s stainless steel pipe, special attention was given to both the L(0,1) mode and L(0,2) mode in this study. It was clearly found that the L(0,2) mode was more sensitive to defects than the L(0,1) mode. Based on the results of the L(0,1) and L(0,2) mode analyses, the magnitude ratio of the two modes was more effective than studying each mode when evaluating defects near the welded zone of stainless steel because of its linear relationship with the length of the artificial defect.

• Proceedings of the KAIS Fall Conference
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• 2012.05b
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• pp.759-761
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• 2012

초음파는 정보 측정분야와 에너지를 이용한 용접 및 가동 등에서 널리 사용되고 있으며 최근에는 이 종금속 접합방법에 있어 초음파 에너지를 이용한 용접이 사용되고 있다. 진공유리 최종공정인 배기공정에 있어 연납과 유리의 접합에 초음파 에너지를 사용하고 있는데 초음파 접합기 하단부의 O링이 열에 의해 변형이 되어 기밀이 유지되지 않게 된다. 본 연구에서는 혼 하단부와 O링의 온도를 최적으로 유지하기 위해 냉각유로를 설치하여 O링의 온도에 미치는 영향에 대해 고찰하였다.

• Journal of Welding and Joining
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• v.16 no.6
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• pp.17-25
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• 1998

• Journal of Welding and Joining
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• v.21 no.4
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• pp.11-18
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• 2003

• Proceedings of the KWS Conference
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• 2000.04a
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• pp.283-286
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• 2000

• Proceedings of the KWS Conference
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• 2003.11a
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• pp.106-109
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• 2003

지능형 초음파 탐상 시스템은 재래식 초음파 탐상시험에서 주된 논란의 대상이 되는 검사의 객관성과 신뢰성, 그리고 일반화된 검사자료의 데이터베이스화 문제를 해결할 수 있는 해법으로 제시 되었다. 또한 이 시스템은 검사의 자동화(혹은 간이자동화)를 통해 검사자에 의해 수작업으로 작성되던 피검체 및 결함관련 정보를 자동으로 계산하고 데이터베이스화함으로써, 열악한 검사환경에서도 최선의 능률을 제공할 수 있는 기반을 제공한다. 본 논문에서는 지능형 시스템의 개발을 위해 필요한 요소기술과 개발된 시스템의 전반에 관하여 논한다.

• Proceedings of the KWS Conference
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• 2007.11a
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• pp.297-299
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• 2007