• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.370-373
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• 1988

Althouah there have been many attempts to control weld quality in resistance spot welding processes, design method for an on-line feedback controller based upon process dynamics has not been suggested. This is due to the fact that the resistance spot welding is a highly complicated process, whice involves the interaction of electrical, thermal, mechanical and metallurgical phenomena. In this paper, an optimal control method based on FDM model with shunt effect is presented, which can regulate the nugget size, at the same time minimizing the control heat input. Optimal PI gain of the controller were determined by numerical optimization. Simulation results show that, as a result of the proposed optimal control, the weld nugget can be made to approach a desired nugget size with less control heat input than that required for the conventional spot welding process in the face of the shunt effect.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.754-758
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• 2005

Optimization of process variables such as arc current, welding voltage and welding speed in terms of the weld characteristics desired is the key step in achieving high quality and improving performance characteristics without increasing the cost. Consequently, incorrect settings of those process variables give rise to deviations in the welding characteristics from the desired bead geometry. Therefore, trainee welders are referred to the tabulated information relating different metal types and thickness as to recommend the desired values of process variables. 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. However, it is difficult for the traditional identification methods to provide an accurate model because the optimized welding process is non-linear and time-dependent. In this paper, the possibilities of the Infra-red sensor in sensing and control of the bead geometry in the automated welding process are presented. Infra-red sensor is a well-known method to deal with the problems with a high degree of fuzziness so that the sensor is employed to build the relationship between process variables and the quality characteristic the proposed above respectively. Based on several neural networks, the mathematical models are derived from extensive experiments with different welding parameters and complex geometrical features. The developed system enables to select the optimal welding parameters and control the desired weld dimensions during arc welding process.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.301-302
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• 2006

In this paper, the possibilities of the Infra-red sensor in sensing and control of the bead geometry in the automated welding process are presented. Infra-red sensor is a well-known method to deal with the problems with a high degree of fuzziness so that the sensor is employed to build the relationship between process variables and the quality characteristic the proposed above respectively. Based on several neural networks, the mathematical models are derived from extensive experiments with different welding parameters and complex geometrical features. The developed system enables to select the optimal welding parameters and control the desired weld dimensions during arc welding process.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.1
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• pp.112-117
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• 2017

The arc, generated by Tungsten Inert Gas(TIG) welding, is stable and provides excellent quality of the weld. Since automation is difficult, a lot of work is performed by hand. In addition, to obtain the uniform weld quality is difficult when using a base metal having a nonuniform welding line, or when welding inside a pipe. Generally, TIG welding power has the characteristic of constant-current. The welding voltage is changed in proportion to the arc length. Hence, the automatic voltage control equipment should be applied at the TIG welding system. The automatic voltage control equipment has been designed using LabVIEW software. It consists of a manufactured voltage divider circuit, and jig for moving the torch. The voltage measurements and driving of the motor were performed through the algorithm implementation in LabVIEW. Welding was conducted while increasing the arc length. In this process, it was confirmed that the automatic voltage control equipment kept the arc length constant.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.9
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• pp.1054-1061
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• 2011

GMA welding process is a production process to improve productivity for the provision of higher quality of material, These includs numerous process variables that could affect welding quality, productivity and cost savings. Recently, the welding part of construction equipment had frequent failure of major components in the welding part of each subsidiary material due to shock which is very poor according to the welding part. Therefore, the implementation of sound welding procedure is the most decisive factor for the reliability of construction machinery. The data generated through experimens conducted in this study has validated its effectiveness for the optimization of bead geometry and process variables is presented. The criteria to control the process parameters, to achieve a healthy bead geometry. This study has developed mathematical models and algorithms to predict or control the bead geometry in GMA fillet welding process.

• Proceedings of the KWS Conference
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• 2002.05a
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• pp.68-70
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• 2002

A CCD camera with a laser strip was applied to realize the automation of welding process in GMAW. The Hough transformation was used to extract the laser stripe and to obtain specific weld points. In this study, a neural network based on the generalized delta rule algorithm was adapted for the process control of GMA, such as welding speed, arc voltage and wire feeding speed.

• Journal of Welding and Joining
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• v.16 no.6
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• pp.97-103
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• 1998

The bracket tilt among automobile parts is weld parts which construct the column assembly bracket tilt of equipments and accurate dimension after welding is more essential than weldment strength. By the way, it is insufficient that systematic study about this parts which have an importance on welding deformation. The reason is that welding deformation is complex problem with shape, size, material of parts and welding sequence, conditions etc. For reduction and removal of welding deformation, therefore, it is necessary that the security of welding deformation data and systematic examination about equipment, costs, work environment, manufacturing process etc. It is all the better that the prediction of welding deformation using simulation of welding process by FEA is supplemented. In this study, the countermeasure for this welding deformation of bracket tilt is brought up through experimental inspection before the choice of the optimum welding conditions with minimum welding deformation by simulation of welding process.

• Journal of Welding and Joining
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• v.13 no.1
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• pp.156-166
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• 1995

Experimental models which are able to determine the deviation between weld line and weaving center by measuring the weld current during welding were proposed for the gas metal arc welding process. The models were used for developing a weld seam tracking system which controls the weaving speed of a welding torch. However, it was revealed that the tracking result of the system is affected by the welding conditions. Thus an arc sensor system was developed by using fuzzy control approach for overcoming the difficulty of modelling the nonlinear process. The rule base and parameters of the fuzzy control system were determined on the basis of the results of experiments. This fuzzy control system has shown the successful tracking capability for the wide operating range of welding conditions.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.289-294
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• 1988

This paper describes tbe design and implementation of the adaptive controller to maintain the glood weld quality in gas metal arc welding process. The weld torch travel speed and the surface temperature are taken, respectively, as an input and an output of the welding control system. Because of the very complex phenomena of the process, the input-output dynamic model was experimentally identified by AIC (Akiake Information Criterion). Based on the model structure, the explicit model reference adaptive controller is simulated in order to regulate the output tempernture to the desired level.