• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.193-201
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• 2021

The welding has a high proportion of the production and drying of ships or offshore plants. Non-destructive testing is carried out to verify the quality of welds in Korea, radiography test (RT) is mainly used. Currently, most shipyards adopt analog-type techniques to print the films through the shoot of welding parts. Therefore, the time required from radiography test to pass or fail judgment is long and complex, and is being manually carried out by qualified inspectors. To improve this problem, this paper covers a platform for scanning and digitalizing RT films occurring in shipyards with high resolution, accumulating them in management servers, and applying artificial intelligence (AI) technology to detect welding defects. To do this, we describe the process of designing and developing RT film scanning equipment, welding inspection information integrated management platform, fault reading algorithms, visualization software, and testing and verification of each developed element in conjunction.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.128.5-128
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• 2001

This paper presents investigation of an arc force sensor for a robotic welding control system. Arc force sensor is employed in this research to monitor the bead geometry of the arc welding process. Arc force sensor mounted at the end of the robot wrist was employed to measure the arc force applied to the weld. Experimental configuration for measurement of arc force was used to quantify the changes in the arc force distributions of the plate being welded. A relationship between the bead dimension and the arc force distributions was established. The sensor information was used to establish a relationship between welding current and arc force. Arc force sensor have shown to be one of the most sophisticated technique to monitor perturbations that occurred during robotic arc welding process.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.289-294
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• 2003

The object of this study is to investigate the effect of compounded welding by using acoustic emission (AE) signals fur weld heat affected zone (HAZ) in tensile testing. This study was carried out a SM 490A high tension steel for electronic shielded metal are welding (SMAW), $\textrm{CO}_2$ gas arc welding and TIG welding. And correspondingly, the root openings are 3, 4 and 2.8mm. Data displays are based on the measured parameters of the AE signals, along with environmental variables such as time and load. These history plots give us useful and powerful information to analyze the results of material evaluation testing.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.1
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• pp.67-76
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• 2013

We present an innovative real-time laser welding monitoring technique employing the correlation analysis of the plasma plume optical emission generated during the process. The plasma optical radiation emitted during Nd:YAG laser welding of S45C steel samples has detected with a Photodiode and analyzed under different process conditions. The discrete DC voltage difference, filter methods and wavelet transform has been used to decompose the optical signal into various discrete series of sequences over different frequency bands. Considering that wavelet analysis can decompose the optical signals, extract the characteristic information of the signals and define the defects location accurately, it can be used to implement process-control of laser welding.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.1
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• pp.79-83
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• 2010

The conventional welding technique such as shield metal arc welding has been mostly applied to the piping system of the nuclear power plants. It is well known that this welding technique causes the overheating and welding defects due to the large groove angle of weld. On the other hand, the narrow gap welding(NGW) technique has many merits, for instance, the reduction of welding time, the shrinkage of weld and the small deformation of the weld due to the small groove angle and welding bead width comparing with the conventional welds. These characteristics of NGW affect the deformation behavior and the distribution of welding residual stress of NGW, thus it is believed that the residual stress results obtained from conventional welding procedure may not be applied to structural integrity evaluation of NGW. In this paper, the welding residual stress of NGW was predicted using the nonlinear finite element analysis to simulate the thermal and mechanical effects of the NGW. The present results can be used as the important information to perform the flaw evaluation and to improve the weld procedure of NGW.

• Journal of IKEEE
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• v.5 no.2 s.9
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• pp.190-200
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• 2001

This paper is addressed to welding defect feature vector selection and implementation method of welding defect classifier using fuzzy techniques. We compare IAV, zero-crossing number as time domain analysis, power spectrum coefficient as frequency domain, histogram as both domain for welding defect feature selection. We choose histogram as feature vector by graph analysis and find out that maximum frequent occurrence number and section of corresponding signal scale in relative histogram show obvious difference between normal welding and voiding with penetration depth defect. We implement a fuzzy welding defect classifier using these feature vector, test it to verify its effectiveness for 695 welding data frame which consist of 4000 sampled data. As result of test, correct classification rate is 92.96%. Lab experimental results show a effectiveness of fuzzy welding defect classifier using relative histogram for practical Laser welding monitoring system in industry.

• Journal of Welding and Joining
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• v.15 no.4
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• pp.1-10
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• 1997

1950년에 최초의 상용 컴퓨터가 도입된 이래 컴퓨터는 모든 사회 분야에 있 어서 필수 불가결한 도구가 되었고 현대의 산업 사회는 정보산업사회라고 할 만큼 정보의 신속한 획득과 정보의 보유량은 산업 경쟁력의 핵심이 되고 있다. 용접 분야 에서도 적절한 용접 정보의 신속한 제공이 용접의 품질과 생산성 향상의 관건이 되고 있으며 최근 용접의 자동화가 급속히 이루어지고 컴퓨터에 의한 통합생산시스템(CIMS, Computer Integrated Manufacturing System)의 구축이 화발해짐에 따라 그들의 핵심 요소의 한 부분으로서 용접 정보처리 시스템의 역활과 중요성은 더욱 커지고 있다.

• Proceedings of the KWS Conference
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• 2008.05a
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• pp.47-47
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• 2008

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.289-294
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• 1988

This paper describes tbe design and implementation of the adaptive controller to maintain the glood weld quality in gas metal arc welding process. The weld torch travel speed and the surface temperature are taken, respectively, as an input and an output of the welding control system. Because of the very complex phenomena of the process, the input-output dynamic model was experimentally identified by AIC (Akiake Information Criterion). Based on the model structure, the explicit model reference adaptive controller is simulated in order to regulate the output tempernture to the desired level.