• 한국레이저가공학회지
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• 제3권2호
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• pp.53-61
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• 2000

On the laser weld production line, a slight alteration of the welding condition produces many defects. The defects are monitored in real time, in order to prevent continuous occurrence of defects, reduce the loss of material, and guarantee good quality. The measurement system is produced by using three photo-diodes for detection of the plasma and spatter signal in CO$_2$ laser welding. For high speed CO$_2$ laser welding, laser tailored welded blanks for example, on-line weld quality monitoring system was developed by using fuzzy multi-feature pattern recognition. Weld qualities were classified optimal heat input, a little low heat input, low heat input, and focus misalignment, and final weld quality were classified good and bad.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2002년도 Proceedings of the International Welding/Joining Conference-Korea
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• pp.595-599
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• 2002

Edge welding of thin sheets is very difficult because of the fit-up problem and small weld area In laser welding, joint fit-up and penetration are critical for sound weld quality, which can be monitored by appropriate methods. Among the various monitoring systems, visual monitoring method is attractive because various kinds of weld pool information can be extracted directly. In this study, a vision sensor was adopted for the weld pool monitoring in pulsed Nd:YAG laser edge welding to monitor whether the penetration is enough and the joint fit-up is within the requirement. Pulsed Nd:YAG laser provides a series of periodic laser pulses, while the shape and brightness of the weld pool change temporally even in one pulse duration. The shutter-triggered and non-interlaced CCD camera was used to acquire a temporally changed weld pool image at the moment representing the weld status well. The information for quality monitoring can be extracted from the monitored weld pool image by an image processing algorithm. Weld pool image contains not only the information about the joint fit-up, but the penetration. The information about the joint fit-up can be extracted from the weld pool shape, and that about a penetration from the brightness. Weld pool parameters that represent the characteristics of the weld pool were selected based on the geometrical appearance and brightness profile. In order to achieve accurate prediction of the weld penetration, which is nonlinear model, neural network with the selected weld pool parameters was applied.

• International Journal of Korean Welding Society
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• 제1권1호
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• pp.7-12
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• 2001

Real time monitoring has become critical as the use of laser welding increases. Plasma and spatter are measured and used as the signal for estimating weld quality. The estimating algorithm was made using the fuzzy pattern recognition with the area of data that is beyond the tolerance boundary. Also, an algorithm that detects the spatter and the localized defect was created in order to kd the partially produced pit and the sudden loss of weld penetration. These algorithms were used in quality monitoring of the $CO_2$ laser tailored blank weld. Statistical program that can display the laser weld quality result and the signal transition was made for the first stage of the remote control system.

• 한국레이저가공학회지
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• 제2권3호
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• pp.19-31
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• 1999

This paper introduces the monitoring scheme of laser welding quality using neural network. The developed monitoring scheme detects light signal emitting from plasma formed above the weld pool with optic sensor and DSP-based signal processor, and analyzes to give a guidance about the weld quality. It can automatically detect defects of laser weld and further give an information about what kind of defects it is, specially partial penetration and porosity among the interior defects. Those could be detected only by naked eyes or X-ray after welding, which needs more processes and costs in mass production. The monitoring scheme extracts four feature vectors from signal processing results of optical measuring data. In order to classify pattern for extracted feature vectors and to decide defects, it uses single-layer neural network with perceptron learning. The monitoring result using only the first feature vector shows confidence rate in recognition of 90%($\pm$5) and decides whether normal status or defects status in real time.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집A
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• pp.791-796
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• 2001

Welding using lasers can be mass-produced in high speed. In the laser welding, performing real-time evaluation of the welding quality is very important in enhancing the efficiency of welding. In this study, the plasma and molten metal which are generated during laser welding were measured using the UV sensor and IR sensor. The results of laser welding were classified into five categories such as optimal heat input, little low heat input, low heat input, focus off, and nozzle change. Also, a system was formulated which uses the measured signals with a fuzzy pattern recognition method which is used to perform real-time evaluation of the welding quality and the defects which can occur in laser welding. Weld quality prediction program was developed using previous weld results and statistical program which could show the trend of weld quality and signal was developed.

• Journal of Welding and Joining
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• 제21권7호
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• pp.34-41
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• 2003

Weld quality monitoring and seam tracking along the butt-joint lengthwise to the tube axis are studied. The material of tube is 60kg/$\textrm{mm}^2$ grade steel sheet, and the longitudinal butt-joint is shaped by 2 roll bending machine. The tube with a thickness of 1.5mm, diameter of 105.4mm and length of 2000mm is successfully obtained by the $CO_2$ laser welding system equipped with a seam tracker and plasma sensor. Experimental results show that the developed welding system can be used for the precision seam tracking and the real-time monitoring of weld quality, and the laser welded tube can be used for car body md component after tubular hydroforming.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.474-478
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• 1996

Process monitoring in laser welding is essential for automation and quality control of products. Various signals from laser welding, such as plasma, sound, optical signals, etc., are utilized for monitoring the process and detecting abnormal weld conditions. In this study, both W light from plasma formed above the weld pool and IR signal from the melting pool are detected with photodiodes and PC-based A/D board, and analyzed to give a guidance about the weld quality. Experimental results show the possibility of using the signals for predicting and evaluating the weld qualify and adapting into the system for on-line process monitoring.

• 한국레이저가공학회지
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• 제5권3호
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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.

• 한국재료학회지
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• 제14권1호
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• pp.1-8
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• 2004

Laser weldability of aluminized steels for deep drawing application has been investigated. Test coupons for Nd:YAG laser welding and $CO_2$ laser welding were prepared trom the commercial steels. According to the test results, total penetration and back bead width of aluminized steels were sensitive to the welding conditions. Bead width at the half thickness of the overlap joint, however, was rather constant. Laser weldability of aluminized steels was superior to that of zinc coated steel. Weld microstructure revealed that overlap zone adjacent to the fusion line was filled with coated materials, which was thought to be desirable to protect weld from crevice corrosion. The aluminum coated materials was also found in the weld metal. Practically no spattering was observed in the laser welding of aluminized steels even when the welding was performed without joint gap. In the welding of zinc coated steel, however, spattering was so severe that it was difficult to get the acceptable weld. Bead quality of aluminized steel laser weld was smooth and stable.

• 한국레이저가공학회지
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• 제2권1호
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• pp.30-37
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• 1999

Laser-welded Tailored Blank is the hottest thing in many automobile companies. But they demand on weld quality, reproducibility, and formability. So it is the great problem of automation of laser welding process. Therefore, it is requested to construct on-line process monitoring system on high accuracy. The light which is emitted from plasma and spatter in laser welding was detected by photo-diodes. It was found that the light intensity depends on welding speed. laser power, and flow rate of assist gas. The relationship between the plasma and spatter and the weld quality can be used for on-line laser weld monitoring systems.