• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.6
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• pp.598-603
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• 2009

Resistance spot welding has been investigated to apply for manufacturing car bodies because of its high productivity. So quality of resistance spot weld is one of the major concerns for both automobile and aerospace industry. Current design trends in automotive manufacture have shifted emphasis to alternative lightweight materials in order to aid in producing vehicles with higher fuel efficiency and lower down the vehicle emission level for environmental control. There is increasing emphasis to provide lighter cars. Therefore there is an effort to use high strength steels such as HSLA, dual phase, in car body. However there is used in restricted because of difficulty in producing consistently high quality resistance spot welds. In this study, resistance spot welding schedules were developed to achieve acceptable welds with improved static mechanical properties. Improved resistance spot welding schedules were developed using post heating current to reduce the cooling rate, or in-process tempering to reduce the hardness of the weld produced. The effects of resistance spot welding process parameter on hardening fracture mode and static mechanical properties of the joints were determined.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.642-646
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• 2000

The use of neural-fuzzy system to model mesh seam welding is described in this paper. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters affecting quality include the arc voltage, the welding current torch travel speed and the pressure and so on. The relationship between the welding parameters and weld quality is not a direct one, md' in addition, the effect of the weld parameter variables are not independent of the each other. The effectiveness of the proposed neuro-fuzzy algorithms is demonstrated by computer simulations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.5
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• pp.937-942
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• 2000

This paper describes for applications of neural networks in the field of arc welding. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters affecting quality include the arc voltage, the welding current and the torch travel speed. The relationship between the welding parameters and weld quality is not a direct one, and in addition, the effect of the weld parameter variables are not independent of the each other - changing the welding current will affect the arc voltage, and so on. Finally, a suitable proposal to improve the construction of the model has also been presented in the paper.

• Journal of Ocean Engineering and Technology
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• v.13 no.2 s.32
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• pp.66-73
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• 1999

This paper presents the experimental examinations and statistical quantitative analysis of the correlation between the cumulative counts of acoustic emission(AE) during plastic deformation periods of the welding and the tensile strength and other properties of the tube-to-tube welded joints of O.D. 30mm (I.D 18mm) nozzle steel. This is a new approach which attempts finally to develop real-time quality monitoring system for friction welding. And this study results in practical possiblility of real-time quality control more than 100% joint efficiency showing good weld no micro structural defects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.4
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• pp.885-893
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• 2000

The use of neural-fuzzy system to model mesh seam welding is described in this paper. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters affecting quality include the arc voltage, the welding current, torch travel speed and the pressure and so on. The relationship between the welding parameters and weld quality is not a direct one, and in addition, the effect of the weld parameter variables are not independent of the each other. The effectiveness of the proposed neuro-fuzzy algorithms is demonstrated by computer simulations.

• Special Issue of the Society of Naval Architects of Korea
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• 2013.12a
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• pp.73-80
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• 2013

From broad point of view, seam tracking has been one of main issues with respect to welding automation. Several attempts have been successful for seam tracking of fixed weaving width. As a solution of the seam tracking methods for varying groove width, the visual sensors such as CCD cameras have been adopted. Although the vision sensing techniques can achieve high accuracy, the weak point is that well-prepared vision sensor environment should be required to obtain high-quality visual measurements which can be easily affected by significant noises in industrial areas. This paper proposed an alternative seam tracking algorithm for narrow groove. A special measurement device for arc voltage, in this study, is developed to enhance the reliability of the measured welding signals. Based on the developed arc sensor algorithm, an automatic weld-width tracking algorithm is also proposed, which is able to predict the weld-position more accurately. The usefulness of the automatic weld-width tracking algorithm was well verified by applying it to gas tungsten arc welding (GTAW).

• Proceedings of the Korean Society of Laser Processing Conference
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• 1999.05a
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• pp.9-13
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• 1999

• Proceedings of the KWS Conference
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• 2006.05a
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• pp.175-177
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• 2006

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.166-166
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• 2000

This paper describes for applications of neural networks in the field of arc welding. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters affecting quality include the arc voltage, the welding current and the torch travel speed. The relationship between the welding parameters and weld qualify is not a direct one, and in addition, the effect of the weld parameter variables are not independent of the each other - changing the welding current will affect the arc voltage, and so on. Finally, a suitable proposal to improve the construction of the model has also been presented in the paper.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1049-1078
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• 2021

The review summarizes the published data on the widely applied electron-beam, laser-beam, as well as resistance upset, projection, and spot welding of zirconium alloys for nuclear applications. It provides the results of their analysis to identify common patterns in this area. Great attention has been paid to the quality requirements, the edge preparation, up-to-date equipment, process parameters, as well as post-weld treatment and processing. Also, quality control and weld repair methods have been mentioned. Finally, conclusions have been drawn about a significant gap between the capabilities of advanced welding equipment to control the microstructure and, accordingly, the properties of welded joints of the zirconium alloys and existing algorithms that enable to realize them in the nuclear industry. Considering the ever-increasing demands on the high-burnup accident tolerant nuclear fuel assemblies, great efforts should be focused on the improving the welding procedures by implementing predefined heat input cycles. However, a lot of research is required, since the number of possible combinations of the zirconium alloys, designs and dimensions of the joints dramatically exceeds the quantity of published results on the effect of the welding parameters on the properties of the welds.