• Proceedings of the KWS Conference
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• 1999.10a
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• pp.142-145
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• 1999

The dynamic resistance monitoring is one of the important issues in that in-process and real time quality assurance of resistance spot weld is needed to increase the product reliability. Secondary dynamic resistance patterns, as a real manner, are hard to adapt those factors in real time and in-plant system. In the present study, a new dynamic resistance detecting method is presented as a practical manner of weld quality assurance at the primary circuit. By the correlation analysis, it is found that the primary dynamic resistance patterns are basically similar to those of the secondary. Various dynamic resistance indices are characterized with the primary curve. And quality of the weld, like the tensile shear strength, is estimated using adaptive neuro-fuzzy estimation system which is consisted of the Sugeno fuzzy algorithm. Through the fuzzy clustering and parameter optimization, real time weld quality assurance system with less efforts is proposed.

• Journal of Welding and Joining
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• v.16 no.5
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• pp.119-133
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• 1998

To implement full automation in pipe welding, it si most important to develop special sensors and their related systems which act like human operator when detecting irregular groove conditions. In this study, an automatic pipe Gas Metal Arc Welding (GMAW) system was proposed to full control pipe welding procedure with intelligent sensor systems. A five-axes manipulator was proposed for welding torch to automatically access to exact welding position when pipe size and welding angle were given. Pool status and torch position were measured by using a weld-pool image monitoring and processing technique in root-pass welding for weld seam tracking and weld pool control. To overcome the intensive arc light, pool image was captured at the instance of short circuit of welding power loop. Captured image was processed to determine weld pool shape. For weld seam tracking, the relative distance of a torch position from the pool center was calculated in the extracted pool shape to move torch just onto the groove center. To control penetration of root pas, gap was calculated in the extracted pool image, and then weld conditions were controlled for obtaining appropriate penetration. welding speed was determined with a fuzzy logic, and welding current and voltage were determined from a data base to correspond to the gap. For automatic fill-pass welding, the function of human operator of real time weld seam control can be substituted by a sensor system. In this study, an arc sensor system was proposed based on a fuzzy control logic. Using the proposed automatic system, root-pass welding of pipe which had gap variation was assured to be appropriately controlled in welding conditions and in torch position by showing sound welding result and good seam tracking capability. Fill-pass welding by the proposed system also showed very successful result by tracking along the offset welding line without any control of human operator.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.2
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• pp.393-406
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• 1993

In resistance spot welding process, size of molten nuggest have been utilized to assess the integrity of the weld quality. However real-time monitoring of the nugget size is an extremely difficult problem. This paper describes the design of an artificial neural networks(ANN) estimator to predict the nugget size for on-line use of weld quality monitoring. The main task of the ANN estimator is to realize the mapping characteristics from the sampled dynamic resistance signal to the actual negget size through training. The structure of the ANN estimator including the number of hidden layers and nodes in a layer is determined by an estimation error analysis. A series of welding experiments are performed to assess the performance of the ANN estimator. The results are quite promissing in that real-time estimation of the invisible nugget size can be achieved by analyzing the dynamic resistance signal without any conventional destructive testing of welds.

• Journal of Welding and Joining
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• v.19 no.4
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• pp.391-398
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• 2001

MIAB welding method uses a rotating arc as its heat source and is known to be efficient in pipe butt welding. The arc is rotated around the weld line by the electro-magnetic force resulting from the interaction of arc current and magnetic field. This paper is concerned with the experiment of initial stage for process control, monitoring for weld quality, and the design of coil system which is efficient of flux generation and concentration. A coil system for the generation of magnetic flux was designed and constructed. Magnetic flux density and arc rotating behavior are important factors in MIAB welding, so the relations between these factors and process parameters were investigated. Various experiments were performed for the steel pipes(48.1mm O.D and 2.0mm thickness). The magnetic flux density is increased by increasing exciting current and decreasing gap size. The maximum of arc rotating frequency is affected by exciting current and gap size. However, the variations of arc rotating frequency during welding and then the melting process are mainly influenced by welding current. Thus, it is considered that the results of this study can be used as important data on the monitoring for weld quality and the design of efficient coil system.

• Proceedings of the KWS Conference
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• 2003.11a
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• pp.52-54
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• 2003

In automotive industry, light weight vehicle is one of issues because of air pollution. Therefore, automotive manufacturers have tried to apply light materials such as aluminum to car body. Welding aluminum using laser has some advantages good weld quality and high productivity. In this study, light emission which is generated in aluminum 6k21 welding with laser is measured using photodiodes. Analysis of relationship between sensor signals of welding variables and formation of keyhole and plasma is performed.

• Proceedings of the KWS Conference
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• 1994.10a
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• pp.111-114
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• 1994

This paper describes a method to measure a weldment surface temperature for estimating variations of the weld pool size in the gas metal arc(GMA) welding processes. An Infrared sensing system is designed to measure the radiation emitted from the top surface of the weldment, The interference effect of the electric arc to the measurement is rejected by detecting the low peaks of the noisy signal. An optimizing criterion, in which the correlation between the weld quality and the measured temperature is maximized, is also proposed to determine the optimal measurement location.

• Laser Solutions
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• v.5 no.3
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• pp.21-30
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• 2002

In automotive industry, the studies about light weight vehicle and improving the productivity have been accomplished. For that, TRIP steel was developed and research for the laser welding process have been performed. In this study, the monitoring system using photodiode was developed for laser welding process of TRIP steel. With measuring light, neural network model for estimating bead width and tensile strength was made and weld quality classification algorithm was formulated with fuzzy inference method.

• Journal of Welding and Joining
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• v.30 no.1
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• pp.44-50
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• 2012

• Proceedings of the Korean Society of Laser Processing Conference
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• 2003.05a
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• pp.39-42
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• 2003

• Proceedings of the KWS Conference
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• 2002.05a
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• pp.62-64
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• 2002