• Journal of Advanced Marine Engineering and Technology
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• 제20권1호
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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.

• 한국안전학회지
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• 제20권1호
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• pp.30-35
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• 2005

This study proposes construction of through transmission for weld defects detection of rail weld zone from ultrasonic signals. For these purposes, the ultrasonic signals for defects(porosity and crack) of weld zone in rails are acquired in the type of time series data and echo strength. 6 lines in the distance amplitude characteristics curve(DACC) indicated damage evaluation standard of weld zone in rails. The acquired ultrasonic signals agree flirty well with the mesured results of reference block and sensitivity block(defect location beam propagation distance, echo strength, etc). The proposed construction of through transmission in this study can be used for weld defects detection of rail weld zone.

• Journal of Welding and Joining
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• 제14권6호
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• pp.58-67
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• 1996

The horizontal filet welding is prevalently used in heavy and ship building industries to join the parts. The phenomena occurring in the horizonal fillet welding process are very complex and highly non-linear, so that its analysis is relatively difficult. Furthermore, various kinds of weld defect such as undercut, overlap, porosity. excess weld metal and incomplete penetration can be induced due to improper welding conditions. Among these defects, undercut, overlap and excess weld metal appear frequently in horizontal filet welding. To achieve a satisfactory weld bead geometry without weld defects, it is necessary to study the effect of welding conditions in the weld bead geometry. For analyzing the weld bead geometry with and without weld defects in horizontal fillet welding, a mathematical model was proposed in conjunction with a two-dimensional heat flow analysis adopted for computing the melting tone in . base metal. The reliability of the proposed model was evaluated through experiments. which showed that the proposed model was very effective for predicting the weld bead shape with or without weld defects in horizontal fillet welding.

• Journal of Welding and Joining
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• 제18권2호
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• pp.204-204
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• 2000

There are many weld defects such as surface crack, lack of fusion, and incomplete penetration(IP) in the butt joint weld of the existing steel bridges. The crack-like defects may significantly reduce the life of the structure. This paper presents the procedure and the results of the fatigue life assessment of the butt joints with weld defects in the existing steel girder bridge. The butt joint welds with incomplete penetration were instrumented with strain gages to determine the stress histogram under normal traffic. Based on the measured stress histogram the crack propagation analysis were performed for the fatigue life assessment. By using the suggested procedure and methodology, one can decide the time of periodic inspection and the necessity of repair of the butt joint welds with serious weld defects in the existing steel bridge. (Received October 1, 1999)

• Journal of Welding and Joining
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• 제18권2호
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• pp.77-85
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• 2000

There are many weld defects such as surface crack, lack of fusion, and incomplete penetration (IP) in the butt joint weld of existing steel bridges. The crack-like defects may significantly reduce the fatigue life of the structure. This paper presents the procedure and the results of the fatigue life assessment of the butt joints with weld defects in the existing steel girder bridge. The butt joint welds with incomplete penetration were instrumented with strain gages to determine the stress histogram under normal traffic. Based on the measured stress histogram the crack propagation analysis were performed for the fatigue life assessment. By using the suggested procedure and methodology, one can decide the time of periodic inspection and the necessity of repair of the butt joint welds with serious weld defects in the existing steel bridge.

• 한국강구조학회 논문집
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• 제11권1호통권38호
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• pp.1-11
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• 1999

본 논문에서는 강구조물의 제작 및 시공에서 용접이음부의 고품질을 확보하기 위하여 강구조물 용접이음부 외부결함의 자동검출에 관한 화상처리 알고리즘을 개발한다. 개발 알고리즘은 광학계의 적절한 배치에 의해 얻어지는 4매의 입력화상을 이용하여 기존의 기법에서 검출할 수 없었던 용접이음부 외부결함을 검출할 수 있음을 보인다. 용접 외부결함이 존재하는 시험편을 제작하고 실험을 통하여 개발 알고리즘의 유용성을 확인하였다. 또한 검출된 용접외부결함의 분류 결과를 육안검사 결과와 비교하였다.

• 한국항해학회지
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• 제23권4호
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• pp.105-114
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• 1999

Generally, though we use the vision sensor or arc sensor in welding process, it is difficult to define the welding parameters which can be applied to the weld quality control. Especially, the important Parameters is Arc Voltage, Welding Current, Welding Speed in arc welding process and they affect the decision of weld bead shape, the stability of welding process and the decision of weld quality. Therefore, it is difficult to determine the unique relationship between the weld bead geometry and the combination of various welding condition. Due to the various difficulties as mentioned, we intend to use Fuzzy Logic and Neural Network to solve these problems. Therefore, the combination of Fuzzy Logic and Neural network has an effect on removing the weld defects, improving the weld quality and turning the desired weld bead shape. Finally, this system can be used under what kind of welding recess adequately and help us make an estimate of the weld bead shape and remove the weld defects.

• 한국공작기계학회논문집
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• 제15권2호
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• pp.87-92
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• 2006

This paper supplements shortcoming of radioactivity check by detecting defect of SWP weld zone using ultrasonic wave. Manufacture 2 stage robot detection systems that can follow weld bead of SWP by method to detect weld defects of SWP that shape of weld bead is complex for this as quantitative. Also, through signal processing ultrasonic wave defect signal system of GUI environment that can grasp easily existence availability of defect because do videotex compose. Ultrasonic wave signal of weld defects develops artificial intelligence style sightseeing system to enhance pattern recognition of weld defects and the classification rate using neural net. Classification of weld defects that do fan Planar defect and that do volume defect of by classify.

• 한국안전학회지
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• 제26권5호
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• pp.17-22
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• 2011

This study proposes feature extraction method of pattern recognition by evaluation of weld defects in weld zone of titanium. For this purpose, analysis objectives in this study are features of attractor quadrant and fractal dimension. Trajectory changes in the attractor indicated a substantial difference in fractal characteristics resulting from distance shifts such as porosity of weld zone. These differences in characteristics of weld defects enables the evaluation of unique characteristics of defects in the weld zone. In quantitative fractal feature extraction, feature values of 0.87 and 1.00 in the case of part of 0.5 skip distance and 0.72 and 0.93 in the case of part of 1.0 skip distance were proposed on the basis of fractal dimensions. Attractor quadrant point, feature values of 1.322 and 1.172 in the case of ${\phi}1{\times}3mm$ porosity and 2.264 and 307 in the case of ${\phi}3{\times}3mm$ porosity were proposed on the basis of distribution value. The Proposed feature extraction of pattern recognition in this study can be used for safety evaluation of weld zone in titanium.

• 한국레이저가공학회지
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• 제2권3호
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• pp.19-31
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• 1999

This paper introduces the monitoring scheme of laser welding quality using neural network. The developed monitoring scheme detects light signal emitting from plasma formed above the weld pool with optic sensor and DSP-based signal processor, and analyzes to give a guidance about the weld quality. It can automatically detect defects of laser weld and further give an information about what kind of defects it is, specially partial penetration and porosity among the interior defects. Those could be detected only by naked eyes or X-ray after welding, which needs more processes and costs in mass production. The monitoring scheme extracts four feature vectors from signal processing results of optical measuring data. In order to classify pattern for extracted feature vectors and to decide defects, it uses single-layer neural network with perceptron learning. The monitoring result using only the first feature vector shows confidence rate in recognition of 90%($\pm$5) and decides whether normal status or defects status in real time.