• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1845-1848
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• 2005

The automatic $CO_2$ welding is a manufacturing process to produce high quality joints for metal and it could provide a capability of full automation to enhance productivity. Despite the widespread use in the various manufacturing industries, the full automation of the robotic $CO_2$ welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this research, an attempt has been made to develop an intelligent algorithm to predict the weld geometry (top-bead width, top-bead height, back-bead width and back-bead height) as a function of key process parameters in the robotic $CO_2$welding. A sensitivity analysis has been conducted and compared the relative impact of three process parameters on bead geometry in order to verify the measurement errors on the values of the uncertainty in estimated parameters.

• Journal of Welding and Joining
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• v.17 no.5
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• pp.40-46
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• 1999

The sensors employed in the robotic are welding system must detect the changes in weld characteristics and produce the output that is in some way related to the change being detected. Such adaptive systems, which synchronise the robot arm and eyes using a primitive brain will form the basis for the development of robotic GMA(Gas Metal Arc) welding which increasingly higher levels of artificial intelligence. The objective of this paper is to realize the mapping characteristics of bead height through learning. After learning, the neural estimation can estimate the bead height desired from the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) are chosen from an estimation error analysis. A series of bead of bead-on-plate GMA welding experiments was carried out in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the bead height with reasonable accuracy and guarantee the uniform weld quality.

• Laser Solutions
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• v.14 no.2
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• pp.1-7
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• 2011

The latest trends of vehicle technology development are fuel efficiency improvement, body designs declining air resistance and lightweight of materials. Especially, as lightened weight of materials makes engine efficient so that vehicles keep the best performance, it is the best way to protect the environment and reduce fuel consumption. In this study, we conducted laser welding by using 3-dimension remote scanner that is 5J32 aluminium alloy. Furthermore, conduction experiment that was 3 times repeated for changing factors such as observing angle, laser power and welding speed. we observed exterior and cross section of weled part and tensile strength. When increasing laser power and decreasing laser speed, tensile strength increased. In order to evaluate factors that affect tensile strength qualitatively we conducted ANOVA. We assumed that the factors are observing angle, laser power and welding speed. Then we found that laser power and laser speed affect tensile strength. We conducted evaluation of weldability of aluminium alloy by above ways.

• Journal of Korean Society of Steel Construction
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• v.9 no.2 s.31
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• pp.237-248
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• 1997

Three types of fatigue cracks frequently observed in the crane runway girders are verified experimentally using two testing-purpose girders with the size of $6400{\times}600{\times}300$ in millimeters. The fatigue cracks are observed in the vicinity of load-bearing points, at the end of gusset plates and at the fillet welded joints between the lower flange and the web. The load-bearing-point cracks are initiated at the intersection of the fillet welds between the upper flange and the web, where the vertical stiffener is located. The cracks grow up toward the diagonal direction of the web. The cracks observed at the fillet welded joints grow up perpendicularly to the crane runway girder. Compared with the JSSC fatigue design code, the joint class is classified as follows: E for the vicinity of load-bearing points, G or H for the end of gusset plates and D for the lower fillet welded joints. The tests reveal that the class of joint classification at the end of gusset plates and at the lower flange coincides with the fatigue design code.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.114-114
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• 2009

최근 국내외에서 자동차 연비와 성능 향상을 위하여 고부가가치 자동변속기의 개발이 적극적으로 추진되고 있다. 특히, 유럽(ZF)과 일본(JATCO, AISIN)을 비롯한 변속기 부품의 기술선진국에서는 전자빔 용접을 적용한 고부가가치 자동변속기 제품이 개발되어 다양한 고급차 모델에 적용되고 있으며 2010년까지 8속 자동변속기를 출시할 예정으로 개발을 추진하고 있다. 이러한 자동변속기를 개발하기 위하여 부품의 성형 및 가공정밀도 관리가 중요하며, 최종 조립되는 부품의 전처리(연질화처리, 탈지, 이물질 제거등)와 용접시 용접변형을 최소화하기 위한 공정조건의 엄격한 관리가 요구되고 있다. 변속기 부품으로 사용되는 소재는 성형성 확보를 위한 연질재(SPCC)와 강도를 확보하기 위한 고강도강(SAPH400, SPFH590)으로 서로 다른 두께의 재질이 조립되어 최종단계에서 용접공정에 의해 제작되고 있다. 특히, 연질재는 복잡한 형상으로 성형한 다음, 가공을 거쳐 경화를 위한 연질화처리가 요구되기 때문에 건전한 용접을 하기 위해서는 용접면에 접한 연질화 처리부는 연질화 처리재가 잔존하지 않도록 완전한 제거할 필요가 있다. 만약 전처리 공정에서 충분한 세척과 가공품의 정도관리가 확보되지 않으면 전자빔 용접시 고온에서 이물질 증발과 잔류, 스패터 발생등에 의한 용접부 결함발생이나 용접변형으로 인하여 제품불량이 발생하게 된다. 따라서 본 연구에서는 최종 조립공정인 용접작업시 발생되는 결함을 방지하고 이 두께 및 이종소재의 전자빔 용접비드 형상(비드 폭, 용입깊이)을 최적화 함으로서 용접부 변형을 최소화하고 충분한 강도를 확보하고자 전자빔 용접전류와 속도에 따른 비드형상을 비교검토 하고자 하였다. 그리고 실차적용시 신뢰성을 확보하기 위하여 전자빔 용접한 자동차 변속기 부품의 비틀림 시험을 실시하였으며 전자빔 용접 전, 후의 변형량을 측정하여 변속기 부품으로서의 적용성을 검증하고자 하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.999-1008
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• 2012

Unlike the existing CMOS chip, ISB (Intelligent Silicon Bead) is new concept biochip equipped with optical communication and memory function. It uses the light for power of SoC CMOS and interface with external devices therefore it is possible to miniaturize a chip size and lower the cost. This paper introduces an input protocol and a design of the low power and the low area to transfer the power and the signal through a single optical signal applied from external reader device to bead chip at the same time. It is also verified through simulation and measurement. In addition, low-power PROM is designed for recording and storing ID of a chip and it is successful in obtaining the value of output according to the optical input. Through this study, a new type biochip development can be expected by solving high cost and a limit of miniaturizing a chip area problem of an existing RFID.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.4
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• pp.62-67
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• 2024

In this paper, we developed and optimized a chitosan-based polymer microbial bead carrier that is cell-friendly, has a high moisture absorption rate, and effectively provides the conditions for microbial biomineral formation as an optimal microbial carrier that protects microorganisms in concrete, and evaluated the self-healing performance of mortar using it. In order to incorporate circular-shaped microbial endospores, a circular-shaped microbial bead carrier was developed by combining chitosan and alginate polymers, and the amount of calcium carbonate produced could be actively controlled by adjusting the composition of the carrier. The amount of biominerals formed and the size of crystals were maximized in the hydrogel bead carrier containing chitosan, and in the case of mortar cracks using this, it was confirmed that self-healing of cracks with a maximum crack width of 0.3mm was achieved within 96 hours after crack generation.

• Applied Chemistry for Engineering
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• v.22 no.4
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• pp.384-389
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• 2011

We made suspension of fumed silica in polyethylene glycol (PEG), studied rheological behavior as functions of contents of silica, dispersion condition, PEG molecular weight, temperature and contents of humidity. Rheological behavior of suspension was determined critical shear rate and rise of viscosity using rheometer AR2000. Suspension were PEGs of molecular weight 200, 400, and 600. Fumed silica suspensions of which silica contents are 5, 7, 9, 13, and 18% were prepared by normal mixing, homogenization and bead milling process. We observed their rheological behaviors at 10, 20, 30, and $40^{\circ}C$. As the PEG molecular weight and contents of silica increase, the critical shear rate was lowered. As the temperature increased, the critical shear rate was increased. Humidity contents of dispersion don't influence on the critical shear rate, but dispersion processes greatly affect the critical shear rate. The critical shear rate of suspensions prepared by the mixing process was the lowest, and that of suspensions prepared by the bead milling process was the highest. The rise in the shear viscosity of suspensions prepared by the mixing process is higher than that of suspensions prepared by the bead milling process. This was dependent on the dispersion condition of silica particle by dispersion process.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.6
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• pp.57-63
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• 1998

An adaptive control in the robotic GMA welding is employed to monitor information about weld characteristics and process parameters as well as to modify those parameters to hold weld quality within acceptable limits. Typical characteristics are the bead geometry, composition, microstructure, appearance, and process parameters which govern the quality of the final weld. The main objectives of this thesis are to realize the mapping characteristics of bead width through learning. After learning, the neural estimation can estimate the bead width desired form the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) are chosen from an estimation error analysis. A series of bead of bead-on-plate GMA welding experiments was carried out in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the bead width with reasonable accuracy and guarantee the uniform weld quality.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.4
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• pp.89-96
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• 2002

This paper aims to develop an intelligent model for predicting top-bead width for the robotic GMA(Gas Metal Arc) welding process using BP(Back-propagation) neural network and multiple regression analysis. Firstly, based on experimental data, the basic factors affecting top-bead width are identified. Then BP neural network model and multiple regression models of top-bead width are established. The modeling methods and procedure are explained. The developed models are then verified by data obtained from the additional experiment and the predictive behaviors of the two kind of models are compared and analysed. Finally the modeling methods, predictive behaviors md the advantages of each models are discussed.