• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 1992년도 특별강연 및 추계학술발표 개요집
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• pp.91-95
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• 1992

The resistance spot welding process has been extensively used for joining of sheet metals, which are subject to variation of many process variables. Many qualitive analyses of sampled process variables have been attempted to predict nugget size. In this paper, dynamic resistance and electrode movement signal which is a good indicative of the nugget size was examined by introducing an artificial neural network estimator. An artificial neural feedforward network with back-propagation of error was applied for the estimation of the nugget size. The prediction by the neural network is in good agreement with the actual nugget size for resistance spot welding of galvanized steel. The results are quite promising in that the quantitative estimation of the invisible nugget size can be achieved without conventional destructive testing of welds.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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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.

• 대한기계학회논문집
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• 제17권2호
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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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• 제11권2호
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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.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 1993년도 특별강연 및 춘계학술발표 개요집
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• pp.115-119
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• 1993

Many qualitive analyses of sampled process variables have been attempted to predict nugget size in resistance spot welding process. In this paper, dynamic resistance and electrode movement signal which is a good indicative of the nugget size was examined by introducing an artificial neural network estimator. An artificial neural feedforward network with back-propagation of error was applied for the estimation of the nugget size. To assess the advantage of this method. results have been compared with conventional regression method.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 추계학술대회
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• pp.301-306
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• 2003

Spot welding is frequently used for industrial purpose, such as automobile and aerospace industries and household appliances due to its high performance. In these day, robotization and systemization of welding process made it possible to produce more precise or smaller electric parts. And when it comes to welding of steel sheet, the size of nugget must be getting smaller. Therefore, welding conditions are limited to avoid defects, such as deformation, damage, weakening of joining area. In this research, the measurement of the nugget size by the nondestructive inspection has been conducted. As a result, the right estimation of the nugget size and void defects, the detection of corona bond near joining area, the selection of the optimum ultrasonic mode, and set up for ultrasonic inspection are studied. From the trustworthy solutions of nugget size estimated by results of measurement, the optimum inspection conditions depending upon the width of welding parts are determined as well.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 추계학술대회 논문집
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• pp.49-53
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• 2004

Thin spot welding is frequently used for industrial purpose, such as automobile and aerospace industries and household appliances due to its high performance. In these days, the systemization of welding process made it possible to produce more precise or smaller electric parts. And when it comes to welding of steel sheets, the size of nugget must be getting smaller. Therefore, welding conditions are limited to avoid defects, such as deformation, damage and weakening of joining area. In this research, thin spot welding establishes the welding conditions, and then the measurement of the nugget size by the nondestructive inspection has been conducted. As a result, the right estimation of the nugget size, the detection of corona bond near joining area, the selection of the optimum ultrasonic mode, and setup for ultrasonic inspection are studied. From the trustworthy solutions of the nugget size estimated by results of measurement, the optimum inspection conditions depending upon the width of welding parts are determined as well.

• International Journal of Automotive Technology
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• 제5권1호
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• pp.55-59
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• 2004

Spot welding is a very important and useful technology in fabrication of thin sheet structures such as the parts in an automobile. However, because the fatigue strength of the spot welding point is considerably lower than that of the base metal due to stress concentration at the nugget edge, the nugget size must be estimated to evaluate a reasonable fatigue strength at a spot welded lap joint. So far, many investigators have experimentally studied the estimation of fatigue strengths of various spot weldments by using a destructive method. However, these destructive methods poses problems so testing of weldments by these methods are difficult. Furthermore, these methods cannot be applied to a real product, and are time and cost consuming, as well. Therefore, there has been a strong, continual demand for the development of a nondestructive method for estimating nugget size. In this study, the effective nugget size in spot weldments have been analyzed by using thermoelastic stress analysis adopting infrared thermography. Using the results of the temperature distribution obtained by analysis of the infared stress due to adiabatic heat expansion under sinusoidal wave stresses, the effective nugget size in spot welded specimens were estimated. To examine the evaluated effective nugget size in spot weldments, it was compared with the results of microstructure observation from a 5％ Nital etching test.

• 대한기계학회논문집A
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• 제24권10호
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• pp.2581-2588
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• 2000

In previous studies, the dynamic resistance, which was calculated by the process variables measured at the electrode of the welding machine, and the electrode displacement were used for quality exa mination. However, in-process usage of such systems is not effective in systems that include a welding gun attached to a robot. In order to overcome such problems, we obtained and used the process variables from the welding machine timer. This would allow us to estimate real time in -process weld quality. For quality estimation, the features were extracted as factors from the primary dynamic resistance patterns, which were measured in t he welding machine timer. The relationship between the indexes and nugget size of the welds was observed through the regression analysis. Using the analyzed factors, a regression model that could estimate nugget diameter was developed. Two regression equations of the model were suggested depending on the factors, and it was showed that the model developed by stepwise method was effective one for weld quality estimation. The developed estimation model was in good linearity with the nugget diameter obtained through the experimentation.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2009년 추계학술발표대회
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• pp.68-68
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• 2009

최근에 자동차 차체 경량화를 목적으로 개발된 고장력강의 용접품질 향상을 위해 인버터 DC 점용접기가 많이 사용되어지고 있다. 본 연구에서는 국내에서 개발된 인버터 DC 용접기를 사용하여 자동차용 590MPa 고장력 냉연강판(CR, SPFC 590RA)과 아연 도금 강판 (GA- EZFFC 590RA)의 용접품질을 평가하였다. 용접에 사용된 기본 조건은 인장 전단 시험을 통하여 결정하였으며, 동저항, 압흔 자국과 너겟 지름, 인장강도와의 관계를 통계적 방법으로 분석하였으며, 이를 활용하여 고장력 강판의 동저항과 압흔 자국에 따라 너겟 지름과 용접강도를 예측하는 비파괴적 용접 품질 평가 방법을 제시하였다.