• Journal of Welding and Joining
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• v.21 no.5
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• pp.513-517
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• 2003

Resistance welding processes are widely used in automotive applications. In particular, Mash-Seam resistance welding is typically used in Tailored Blank process. If spot welds are changed to a continuous weld, it's easy to reduce noise and to be more stable in cars. A arc welding, laser welding, seam welding using wheel electrode are available to make continuous welds on a car body, but they demand operator with advanced skills and expensive cost to develop. Therefore, flat electrode continuous mash-seam resistance welding process has been used to improve the weak points in currently available system in lap seam welding. This developed process has much more strength and air tightability, and also has much better plastic workability than laser welding. Moreover, commercial RSW machine can be readily used in this welding process.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.362-366
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• 1990

The resistance spot welding process has been extensively used for joining of sheet metals, which are subject to variation of many process variables. Many qualitative analyses of sampled process variables have been successfully attempted to achieve a uniform nugget size. In this paper, the electrode movement signal which is a good indicative of the nugget size was examined by introducing a mathematical model with four parameters. A neural network method was applied for the estimation of the nugget size by four parameters. The prediction by the neural network is in good agreement with the actual nugget size. The results are quite promising in that the qualitative estimation of the invisible nugget size can be achieved without destructive testing of the welds.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.132-140
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• 1999

This paper suggests a monitoring method for the pulsed laser spot welding of the thin metal sheets using a point IR(InfraRed) sensor. A new criterion was introduced and the experimental results guaranteed the efficiency. The ideal radiation feature was derived from the mathematical model and was simulated. The radiation feature is robust to withstand the change of measuring condition and can be used to detect the absorbed laser energy. In an experiment, the radiation feature was examined for the differect laser energy. The pulse width and the laser power was variated and the radiation feature was examined. In the other experiment, the relationship between the weld strength and radiation feature was examined. Artificial Neural Network(ANN) was employed to find out the relationship. The correlation coefficient between the real strength and the estimated strength is high as 0.94 and the mean square error is low as 0.64 kgf learned parts. Another group of the welds was used to appraise the learning efficiency. The correlation coefficient between the measured and the estimated weld strength is high as 0.91.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.7
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• pp.597-601
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• 2008

Currently knowledge of strain in welds has mainly been obtained from strain gaging method: that is directly attaching most of the material to the gage. The very few non-contact methods are still in the early stage. One of the non-contact methods is by the use of the laser that has high-level of the accuracy for the measurement, and this laser also has excellent characteristics on which many studies for its applications are focused throughout the many fields. A method of study is on the measurement of the strain caused by the characteristics of the spot welded zone which is used with 3-D ESPI system that is functionally modified through the laser ESPI(Electronic Speckle Pattern Interferometry) system. This system employed the SGCC 1.2t which are mainly used for the steel plate such as automobile, structure, building material and electronic appliances.

• 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.11 no.2
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• pp.27-41
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• 1993

The estimation of nugget sizes was attempted by utilizing the artificial neural networks method. Artificial neural networks is a highly simplified model of the biological nervous system. Artificial neural networks is composed of a large number of elemental processors connected like biological neurons. Although the elemental processors have only simple computation functions, because they are connected massively, they can describe any complex functional relationship between an input-output pair in an autonomous manner. The electrode head movement signal, which is a good indicator of corresponding nugget size was determined by measuring the each test specimen. The sampled electrode movement data and the corresponding nugget sizes were fed into the artificial neural networks as input-output pairs to train the networks. In the training phase for the networks, the artificial neural networks constructs a fuctional relationship between the input-output pairs autonomusly by adjusting the set of weights. In the production(estimation) phase when new inputs are sampled and presented, the artificial neural networks produces appropriate outputs(the estimates of the nugget size) based upon the transfer characteristics learned during the training mode. Experimental verification of the proposed estimation method using artificial neural networks was done by actual destructive testing of welds. The predicted result by the artifficial neural networks were found to be in a good agreement with the actual nugget size. The results are quite promising in that the real-time estimation of the invisible nugget size can be achieved by analyzing the process variable without any conventional destructive testing of welds.

• Journal of the Society of Naval Architects of Korea
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• v.29 no.4
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• pp.214-226
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• 1992

In this paper, the characteristics of fatigue crack growth in the spot welded joint of the same kinds of specimens($HS{\times}HS,\;GA{\times}GAB$) and different kinds of specimens($HS{\times}GA,\;HS{\times}GAB$) which consist of dual phase high strength steel(HS) and monogalvanized steel(GA) were examined with static tension tests and axial tension fatigue tests. Some of the important results are as follows : 1. The divergence of tensile strengths among the same and different kinds of spot welds under the same conditions is comparatively low regardless of the difference of stiffness. 2. At the low load bevel and long life legion, the fatigue crack is initiated near the nugget. However, in the high load level and short life region, it occurs a tittle far from the nugget. 3. It has shown a linear relation between maximum stress Intensity factor, Kmax and fatigue life, $N_f$ among each of the spot welds and has gathered in a narrow band on the log-log graph paper. $Kmax=H{\cdot}{N_f}^{P}$ where H and P are a material constant.

• Journal of Welding and Joining
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• v.33 no.2
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• pp.69-77
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• 2015

High strength steels have been continually being developed to improve in fuel economy in automotive and ensure safety of passengers. New bonding and welding methods have been required for improving weldability on high strength steels. In this study, resistance spot welding and Weld-bond with nugget diameters of 4.0mm, 5.0mm, 6.0mm and 7.0mm were produced and tested, respectively. In order to confirm the effect of nugget diameters on tensile shear characteristic of the Weld-bond, tensile shear characteristics of Weld-bond were compared with those of resistance spot welding and adhesive bonding. Peak load of Weld-bond were increased as the nugget diameter increases. After appearing maximum peak load continuous fracture followed with second peak owing to load being carried by resistance spot weldment. Fracture modes of the adhesive layer in Weld-bond fractures were represented by mixed fracture mode, which are cohesive failure on adhesive part and button failure at resistance spot welds. The results showed that the tensile shear properties can be improved by applying Weld-bond on TRIP steel, and more apparent with nugget diameter higher than 5${\surd}$t.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.68-68
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• 2009

Recently, resistance spot welding using Inverter DC is applied to improve the weldability of high strength steel for the auto-body fabrication. In this study, inverter DC spot welding machine, which is developed in the domestic, was evaluated weldability of the galvanized and cold rolled dual-phase steel(tensile strength : 590MPa). The welding conditions (welding time, current and force) were decided by tensile-shear test, and welding strength and nugget size were analyzed by statistical analysis methods which involved dynamic resistance and indentation. The results of the statistical analysis was utilized for real-time estimation of the invisible nugget size and tensile strength. Moreover, it can be achieved without the conventional destructive testing of welds.

• Korean Journal of Metals and Materials
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• v.46 no.8
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• pp.495-505
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• 2008

With the high proportion of zinc coated steels in body-in-white assembly, newly developed surface roughness textured galvannealed steel sheets have been introduced. In this study, zinc coated and surface roughness textured steel sheets were welded by resistance spot welding to investigate its weldability including electrode wear test. Based on the results of tensile-shear test, nugget diameter changes, and electrode tip growth test, it was clear that both surface roughness textured steels (GA-T and GA-E) showed good weldability. Also, there was no large difference in weldability and electrode wear behavior between GA-T and GA-E steels which have different surface roughness morphology. An analysis of electrode degradation showed Fe and Zn penetration through the electrode tip surface at 2400 welds reached $55{\sim}60{\mu}m$ and $75{\sim}80{\mu}m$, respectively. Therefore, there is no significant effect of surface roughness morphology on spot weldability of surface roughness textured galvannealed steel sheets. However, slight difference in thickness of alloying layers existing on electrode tip was found between GA-T and GA-E steels.