• Laser Solutions
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• v.3 no.2
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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.

• International Journal of Korean Welding Society
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• v.1 no.1
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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.

• Journal of Welding and Joining
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• v.1 no.2
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• pp.69-75
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• 1983

Both in-process quality control and reliability of the weld is one of the major concerns is applying friction welding. No reliable nondestructive monitoring method is available at present to determine the weld quality particularly in process of production. So that, this paper presents an experimental examination and quantitative analysis for the effects of initial acoustic emission(AE) counts on the weld strength relating to the rotating speed as a new approach which attempts finally to develop an on-line quality monitoring system design for friction welds using AE techniques. As one of the important results, it was well confirmed that the initial AE counts occurring during plastic deformation period of welding were quantitatively correlated with reliability at 95% confidence level to the joint strength of welds, tube-to-tube (SM 20 C to STS 304) and then an AE technique using the initial AE counts can be reliably applied to in-process strength monitoring of the weld.

• Laser Solutions
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• v.2 no.3
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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.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.1294-1298
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• 2007

Welding process monitoring is advantageous for maintaining weld quality and numerous sensing techniques have been developed for laser welding. Coaxial image monitoring enables direct monitoring of the weld pool shape and keyhole behavior, but requires the complex optical system and the image processing technique. In this study, we coaxially acquired the weld pool images during laser lap welding by using the camera and special illumination. The welding characteristics - pool width and length, keyhole shape, etc - were extracted by using image processing and the relationship between these characteristics and the penetration depth were investigated.

• Journal of Welding and Joining
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• v.27 no.6
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• pp.9-16
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• 2009

In this paper, the coaxial monitoring system to capture image of weld pool was developed in laser-arc hybrid welding. In order to obtain the reliable image, green laser was used as a illumination system and measuring components such as band pass filter, ND (Neutral Density) filter and shutter speed was designed and optimized. Using this monitoring system, weld pool images were captured according to laser power, welding speed, welding current and interspace between laser and arc through the experiment. ANOVA (Analysis of Variation) was carried out to identify the influence of process variables on bead widths extracted from captured images of monitoring system. Welding speed and current were major factor to affect weld pool.

• Journal of Welding and Joining
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• v.20 no.1
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• pp.26-33
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• 2002

This study was undertaken to obtain the fundamental knowledges on the weld deflects and it's realtime monitoring method. The paper describes the results of high speed photography, acoustic emission (AE) detection and plasma light emission (LE) measurements during $CO_2$ laser welding of STS 304 stainless steel and A5083 aluminum alloy in different welding condition. The characteristic frequencies of plasma and keyhole fluctuations at different welding speed and shield gases were measured and compared with the results of Fourier analyses of temporal AE and LE spectra, and they had considerably good agreement with keyhole and plasma fluctuation. Namely, the low frequency peaks of AE and LE shifted to higher frequency range with the welding speed increase, and leer the argon shield gas it was higher than that in helium and nitrogen gases. The low frequencies dominating in fluctuation spectra of LE probably reflect keyhole opening instability. It is possible to monitor the weld bead deflects by analyzing the acoustic and/or plasma light emission signals.

• Laser Solutions
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• v.2 no.1
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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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.7
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• pp.1326-1331
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• 2006

Weld root gap is a important fact of a falling-off weld quality in various kind of weld defect. The welding quality can be controlled by monitoring important parameters, such as, the Arc voltage, welding current and welding speed during the welding process. Welding systems use either a vision sensor or an Arc sensor, both of which are unable to control these parameters directly. Therefore, it is difficult to obtain necessary bead geometry without automatically controlling the welding parameters through the sensors. In this paper we propose a novel approach using neural networks for detecting and monitoring of weld root gap and bead shape. Through experiments we demonstrate that the proposed system can be used for real welding processes. The results demonstrate that the system can efficiently estimate the weld bead shape and detect the welding defects.

• Journal of Welding and Joining
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• v.21 no.7
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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.