• Journal of Welding and Joining
• /
• v.2 no.1
• /
• pp.25-29
• /
• 1984

In order to investigate the predominant factors which determine penetration depth and bead width in electron beam welding, bead-on-plate welding was carried out using 7075-T6 Al alloy. The results obtained from the present experiments can be summarized as follows; 1) With increasing accelerating voltage, bead width (B.W) decreases but penetration increases remarkably. 2) Increasing beam current results in increase of bead width and penetration respectively, and decrease of the ratio of penetration increment to beam current increment. 3) With increasing welding speed penetration decreases remarkably, while bead width creases.

• International Journal of Korean Welding Society
• /
• v.1 no.2
• /
• pp.12-17
• /
• 2001

With the advance of the robotic welding process, procedure optimization that selects the welding procedure and predicts bead width that will be deposited is increased. A major concern involving procedure optimization should define a welding procedure that can be shown to be the best with respect to some standard and chosen combination of process parameters, which give an acceptable balance between production rate and the scope of defects for a given situation. This paper presents a new algorithm to establish a mathematical model f3r predicting bead width through a neural network and multiple regression methods, to understand relationships between process parameters and bead width, and to predict process parameters on bead width for GMA welding process. Using a series of robotic arc welding, additional multi-pass butt welds were carried out in order to verify the performance of the neural network estimator and multiple regression methods as well as to select the most suitable model. The results show that not only the proposed models can predict the bead width with reasonable accuracy and guarantee the uniform weld quality, but also a neural network model could be better than the empirical models.

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

• Journal of Welding and Joining
• /
• v.18 no.4
• /
• pp.48-54
• /
• 2000

Adaptive control in the robotic GMA(Gas Metal Arc) welding is employed to monitor information about weld characteristics and process parameters as well; as t modify those parameters to hold weld. The objectives of this paper are to realize the mapping characteristics of bead width through the neural network and multiple regression method as well as to select the most accurate model in order to control the weld quality(bead width0. The experimental results show that the proposed neural network estimator can predict bead width with reasonable accuracy, and guarantee the uniform weld quality.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.16 no.4
• /
• pp.79-86
• /
• 2007

The shape of excessive penetration mainly depends on welding conditions(welding current and welding voltage), and welding process(groove gap and welding speed). These conditions are the major affecting factors to width and height of back bead. In this paper, back-bead prediction and weldability estimation using artificial neural network were investigated. Results are as follows. 1) If groove gap, welding current, welding voltage and welding speed will be previously determined as a welding condition, width and height of back bead can be predicted by artificial neural network system without experimental measurement. 2) From the result applied to three weld quality levels(ISO 5817), both experimented measurement using vision sensor and predicted mean values by artificial neural network showed good agreement. 3) The width and height of back bead are proportional to groove gap, welding current and welding voltage, but welding speed. is not.

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

• Journal of Welding and Joining
• /
• v.24 no.5
• /
• pp.37-42
• /
• 2006

The robotic arc welding is widely employed in the fabrication industry fer increasing productivity and enhancing product quality by its high processing speed, accuracy and repeatability. Basically, the bead geometry plays an important role in determining the mechanical properties of the weld. So that it is very important to select the process variables for obtaining optimal bead geometry. In this paper, the possibilities of the Infrared camera in sensing and control of the bead geometry in the automated welding process are presented. Both bead width and thermal images from infrared thermography are effected by process parameters. Bead width and isotherm radii can be expressed in terms of process parameters(welding current and welding speed) using mathematical equations obtained by empirical analysis using infrared camera. A linear relationship exists between the isothermal radii producted during the welding process and bead width.

• Proceedings of the KWS Conference
• /
• 2006.10a
• /
• pp.271-273
• /
• 2006

This paper focuses on the developed empirical models for the prediction on top-bead width in GMA(Gas Metal Arc) welding process. Three empirical models have been developed: linear, curvilinear and an intelligent model. Regression analysis was employed fur optimization of the coefficients of linear and curvilinear model, while Genetic Algorithm(GA) was utilized to estimate the coefficients of intelligent model. Not only the fitting of these models were checked, but also the prediction on top-bead width was carried out. ANOVA analysis and contour plots were respectively employed to represent main and interaction effects between process parameters on top-bead width.

• Proceedings of the Korean Society of Marine Engineers Conference
• /
• 2006.06a
• /
• pp.167-168
• /
• 2006

This paper is concerned about the development system that the bead width's size can be controlled. In order to control the bead width, DC motor driving slide on auto carriage is used. The adjustment of bead width is carried by amplitude and weaving shape is controlled by MCU(Micro Controller Unit). We confirmed the result by tracking experiments.

• International Journal of Automotive Technology
• /
• v.7 no.1
• /
• pp.109-114
• /
• 2006

Half-beads of multi-layer-steel cylinder head gaskets take charge of sealing of lubrication oil and coolant between the cylinder head and the block. Since the head lifts off periodically due to the combustion gas pressure, both the dynamic sealing performance and the fatigue durability are essential for the gasket. A finite element model of the halfbead has been developed and verified with experimental data. The half-bead forming process was included in the model to consider the residual stress effects. The model is employed to assess the dependence of the sealing performance and the fatigue durability on the design parameters of half-bead such as the width and height of bead and the flat region length. The assessment results show that the sealing performance can be enhanced without significant deterioration of the fatigue durability in a certain range of the half-bead width. In the other cases the improvement of sealing performance is accompanied by the loss of the fatigue durability. Among three parameters, the bead width has the strongest influence.