• Proceedings of the KWS Conference
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• 2002.10a
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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.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.307-313
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• 2002

This paper describes a weld pool monitoring technique, which is based on the weld pool image analysis. The proposed image analysis algorithm uses machine vision techniques to extract geometrical information from the weld pool image such as maximum weld pool width, gap width and misalignment between the joint longitudinal axis and the welding wire. These can be related to the welding parameters (welding voltage and current, wire feed speed and standoff) to produce control actions necessary to ensure that the required weld quality will be achieved. The experiments have shown that the algorithm is able to produce good estimates of the weld pool geometry; however, the adjustment of the camera parameters affects the image quality and, consequently, has a great influence over the estimation.

• Laser Solutions
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• v.2 no.2
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• pp.18-26
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• 1999

An innovative real-time weld monitoring technique using chromatic filtering of the thermal radiation from a weld pool is developed. The thermal radiation from the weld pool is focused on an aperture and the transmitted thermal radiation is monitored at two wavelengths with high-speed single-element detectors. Due to the chromatic aberration introduced in the focusing optics, the transmittance curve of thermal radiation varies by the wavelength. Owing to this difference in the transmittance, the local variation of thermal radiation from the weld pool can be monitored by processing the two spectroscopic signals from two detectors. In this paper, the algorithms to monitor the laser power on the weld specimen and the focus shift we investigated and the performances of laser power and focus monitoring are shown for a pulsed Nd:YAG laser welding. The monitoring of the weld pool size variation is also discussed.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.531-536
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• 1992

In GMA welding processes, monitoring and control of weld quality are extremely difficult problems. This paper describes a neural network-based method for monitoring and control of weld pool sizes. First, weld pool sizes are estimated via a neural estimator using multi-point surface temperatures, which are strongly related to the formation of weld pool, and then controlled using the estimated pool sizes. Two types of controllers using the pool size estimator are designed and tested. To evaluate the performance of the designed controllers, a series of simulation studies was performed.

• Journal of Welding and Joining
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• v.12 no.1
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• pp.59-72
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• 1994

This paper presents an on-line quality monitoring and control method to obtain a uniform weld quality in gas metal arc welding (GMAW) processes. The geometrical parameters of the weld pool such as the top bead width and the penetration depth plus half back width are utilized to assess the integrity of the weld quality. Since a good quality weld is characterized by a relatively high depth-to-width ratio in its dimensions, the second geometrical parameter is regulated to a desired one. The monitoring variables are the surface temperatures measured at various points on the top surface of the weldment which are strongly related to the formation of the weld pool The relationship between the measured temperatures and the weld pool size is implemented on the multilayer perceptrons which are powerful for realization of complex mapping characteristics through training by samples. For on-line quality monitoring and control, it is prerequisite to estimate the weld pool sizes in the region of transient states. For this purpose, the time history of the surface temperatures is used as the input to the neural estimator. The control purpose is to obtain a uniform weld quality. In this research, the weld pool size is directly regulated to a desired one. The proposed controller is composed of a neural pool size estimator, a neural feedforward controller and a conventional feedback controller. The pool size estimator predicts the weld pool size under growing. The feedforward controller compensates for the nonlinear characteristics of the welding process. A series of simulation studies shows that the proposed control method improves the overall system response in the presence of changes in torch travel speed during GMA welding and guarantees the uniform weld quality.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1404-1407
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• 1996

A quality monitoring system in butt welding process is proposed to estimate weld pool sizes. The geometrical parameters of the weld pool such as the top bead width and the penetration depth plus half back width are utilized to prove the integrity of the weld quality. The monitoring variables used are the surface temperatures measured at three points on the top surface of the weldment. The temperature profile is assumed that it has a gaussian distribution in vertical direction of torch movement and verify this assumption through temperature analysis. A neural network estimator is designed to estimate weld pool size from temperature informations. The experimental results show that the proposed neural network estimator which used gaussian distribution as temperature information can estimate the weld pool sizes accurately than used three point temperatures as temperature information. Considering the change of gap size in butt welding, the experiment were performed on various gap size.

• 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 the Optical Society of Korea
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• v.4 no.2
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• pp.94-99
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• 2000

Optical monitoring using the chromatic aberration of focusing optics is applied to auto-focus control in laser welding. The spectral transmittance of thermal radiation from a weld pool through an aperture depends on the wavelength of the spectral band and on the distance of the weld pool from the focusing optics. Its dependence has been used to monitor the focus shift in laser welding by measuring the spectral band signals filtered by the aperture. The difference between pulsed and continuous laser welding is analyzed. Furthermore, the dependence of the focus shift monitoring on the weld pool size variation is optimized to monitor the focus shift independently from the laser power change at the weld pool. The performance of the auto-focus control with chromatic filtering is presented for pulsed laser welding.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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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.