http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
김일수,김학형,장한기,김희진,곽성규,유회수,심지연,Kim, Ill-Soo,Kim, Hak-Hyoung,Jang, Han-Kee,Kim, Hee-Jin,Kwak, Sung-Kyu,Ryoo, Hoi-Soo,Shim, Ji-Yeon 대한용접접합학회 2009 대한용접·접합학회지 Vol.27 No.4
In the process to manufacture for metallic structures, control of welding deformation is one of an important problems connected with reliability of the manufactured structures so that welding deformation should be measured and controlled with quickly and actively. Also, welding parameters which have as lot of effects on welding deformation such as arc voltage, welding current and welding speed can also be controlled. The objectives for this study were to develop a simple 2-D FEM to calculate not only the transient thermal histories but also the sizes of fusion and heat-affected zone (HAZ) in multi pass arc welds including the butt and fillet weld type with dissimilar thickness, and to concentrate on a developed model for the finding the parameters of Godak's moving heat source model based on a GA. The developed model includes a GA program using MATLB and GA toolbox, and a batch mode thermal model using ANSYS software. Not only the thermal model was verified by comparison with Goldak's work but also the developed model was validated with molten zone section experimental data.
김일수(Kim Ill-Soo),김학형(Kim Hak-Hyoung),조선영(Cho Sun-Young),강봉용(Kang Bong-Yeong),강문진(Kang Mun-Jin),유관종(You Kwan-Jong) 한국생산제조학회 2004 한국생산제조시스템학회 학술발표대회 논문집 Vol.2004 No.4
Over the last few years, there has been a growing interest in quantitative representation eld pools in order to relate the processing conditions to the driving forces of the welding produced and to use this information for the optimization of the welding process. A theoretical model offers a powerful alternative to check the physical concepts of the welding process and the effects of driving forces. To solve this problem, a 2-D thermo-fluid model were developed for determining temperature and velocity distribution for the GMA welding process.
손준식,김일수,김학형,Son, Joon-Sik,Kim, Ill-Soo,Kim, Hak-Hyoung 대한용접접합학회 2007 대한용접·접합학회지 Vol.25 No.6
Recently, several models to control weld quality, productivity and weld properties in arc welding process have been developed and applied. Also, the applied model to make effective use of the robotic GMA(Gas Metal Arc) welding process should be given a high degree of confidence in predicting the bead dimensions to accomplish the desired mechanical properties of the weldment. In this study, a development of the on-line learning neural network models that investigate interrelationships between welding parameters and bead width as well as apply for the on-line quality control system for the robotic GMA welding process has been carried out. The developed models showed an excellent predicted results comparing with the predicted ability using off-line learning neural network. Also, the system will extend to other welding process and the rule-based expert system which can be incorporated with integration of an optimized system for the robotic welding system.
김일수(Ill-Soo Kim),유관종(Kwan-Jong Yu),서주환(Joo-Hwan Se),손준식(Joon-Sik Son),김학형(Hak-Hyoung Kim) 한국생산제조학회 2006 한국생산제조시스템학회 학술발표대회 논문집 Vol.2006 No.5
The GMA welding process involves large number of interdependent variables which may affect product quality, productivity and cost effectiveness. The relationship between process parameters for a fillet welding and bead geometry is complex because a number of process parameters are involved. To make the automated GMA welding, it is essential that a mathematical model that predicts bead geometry and accomplishes the desired mechanical properties of the weldment is developed. In this paper, an attempt has been made to develop a neural network model and two regression equations(linear and curvilinear) to predict a bead height on fillet welding and to compare the neural network model and the two regression equations in order to select an optimal prediction model.
김지선(Ji-Sun Kim),김일수(Ill-Soo Kim),정재원(Jae-Won Jeong),김학형(Hak-hyoung Kim) 대한기계학회 2009 대한기계학회 춘추학술대회 Vol.2009 No.5
Recently, the improvement of computer capacities and artificial intelligence ware caused to employ for prediction of bead geometry. There are a lot of researches regarding the measurement and prediction of bead geometry for weldment using a neural network in the advanced countries. The objective of this paper is to develop the algorithm that enables the determination of process parameters from the optimized bead geometry for robotic GMA welding using multiple regression analysis and neural network. The experimental results show that the proposed algorithms can predict the bead height with reasonable accuracy and guarantee the uniform weld quality.
김일수(Ill-Soo Kim),유관종(Kwan-Jong Yu),서주환(Joo-Hwan Se),손준식(Joon-Sik Son),김학형(Hak-Hyoung Kim) 한국생산제조학회 2006 한국공작기계학회 춘계학술대회논문집 Vol.2006 No.-
The GMA welding process involves large number of interdependent variables which may affect product quality, productivity and cost effectiveness. The relationship between process parameters for a fillet welding and bead geometry is complex because a number of process parameters are involved. To make the automated GMA welding, it is essential that a mathematical model that predicts bead geometry and accomplishes the desired mechanical properties of the weldment is developed. In this paper, an attempt has been made to develop a neural network model and two regression equations(linear and curvilinear) to predict a bead height on fillet welding and to compare the neural network model and the two regression equations in order to select an optimal prediction model.