• Proceedings of the KWS Conference
• /
• 1996.10a
• /
• pp.139-141
• /
• 1996

Among various welding parameters, the welding current which is inversely proportional to the tip-to-workpiece distance in GMAW is an essential parameter to monitor the GMAW process of horizontal fillet joints. For the case of weld defect such as overlap in horizontal fillet welding, therefore, the signal processing for process monitoring or automatic seam tracking should be modified by considering the weld pool surface geometry including the corresponding weld defect. In other words, the adequate signal processing algorithm is indispensible to improve the performance of the arc sensor. However, arc sensor algorithm already developed usually focus on weld seam tracing but do not considering the weld qualities. In this paper, various experiments were carried out to investigate the tendencies of the weld defects when weaving motion is added, and the experimental method based on 2$^n$ factorial design was proposed for deriving the mathematical model between the leg length and the various welding conditions. Moreover, a signal processing method based on the artificial neural network(Adaptive Resonance Theory) was proposed far discriminating the current signal of sound weld beads from that of weld beads with overlap. Finally, the algorithm for weld seam tracking combined with the mathematical modeling and the signal processing method was carried out to track the weld line in conjunction with the improvement of the weld qualities. The reliability of the proposed algorithms were evaluated through various experiments, which showed that the proposed algorithms could be effectively used for arc welding automation.

• KIISE Transactions on Computing Practices
• /
• v.22 no.5
• /
• pp.235-239
• /
• 2016

'Commit-bug link', the link between commit history and bug reports, is used for software maintenance and defect prediction in bug tracking systems. Previous studies have shown that the links are automatically detected based on text similarity, time interval, and keyword. Existing approaches depend on the quality of commit history and could thus miss several links. In this paper, we proposed a technique to link commit and bug report using not only messages of commit history, but also the similarity of files in the commit history coupled with bug reports. The experimental results demonstrated the applicability of the suggested approach.

• Journal of the Korean Society for Precision Engineering
• /
• v.23 no.10
• /
• pp.7-13
• /
• 2006

• Journal of Welding and Joining
• /
• v.21 no.1
• /
• pp.60-65
• /
• 2003

At present. welding of most pipes with large diameter is carried out by the manual process. Automation of the welding process is necessary f3r the sake of consistent weld quality and improvement in productivity. In this study, two vision sensors, based on the optical triangulation, were used to obtain the information for seam tracking and detecting the weld defects. Through utilization of the vision sensors, noises were removed, images and 3D information obtained and positions of the feature points detected. The aforementioned process provided the seam and leg position data, calculated the magnitude of the gap, fillet area and leg length and judged the weld defects by ISO 5817. Noises in the images were removed by using the gradient values of the laser stripe's coordinates and various feature points were detected by using an algorithm based on the iterative polygon approximation method. Since the process time is very important, all the aforementioned processes should be conducted during welding.

• Proceedings of the KIEE Conference
• /
• 2006.07d
• /
• pp.1973-1974
• /
• 2006

The mean shift algorithm has achieved considerable success in object tracking due to its simplicity and robustness. It finds local maxima of a similarity measure between the color histograms of the target and candidate image. However, the mean shift tracking algorithm using only color histograms has a serious defect. It doesn't use the spatial information of the target. Thus, it is difficult to model the target more exactly. And it is likely to lose the target during the occlusions of other objects which have similar color distributions. To deal with these difficulties we use both color information and spatial information of the target. Our proposed algorithm is robust to occlusions and scale changes in front of dynamic, unstructured background. In addition, our proposed method is computationally efficient. Therefore, it can be executed in real-time.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.6
• /
• pp.229-236
• /
• 2022

Based on the Internet of Things, a web system that can check the condition around the fire extinguisher, whether a fire has occurred, and an application that can receive fire notifications in real time is implemented. Minimize errors that occur during development by using software engineering to clarify the goals of the system and define the structure in detail. In addition, for IoT-based fire extinguishers, a method of reducing defects by finding product defects in the demand analysis, design, and implementation stages and analyzing the cause thereof is proposed. Through the proposed research, it is possible to secure the reliability of defect management for IoT-based smart fire extinguisher.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.3
• /
• pp.117-125
• /
• 2024

In this paper, implement and propose an Active Electronically Scanned Array (AESA) radar integration analysis system which specialized for radar development by using heterogeneous media. Most analysis systems are used to analyze and improve the cause of defects, so they help the test easier. However, previous log analysis systems that operate only based on text are not intuitive and difficult to find the information user want at once if there is a lot of log information. so when an equipment defect occurs, there are limitations in analyzing the cause of defect. Therefore, the analysis system in this paper utilizes heterogeneous media. The media defined in this paper refers to recording text-based data, displaying data as image or video and visualizing data. The proposed analysis system classifies and stores data that transmitted and received between radar devices, radar target detection and Tracking algorithm data, etc. also displays and visualizes radar operation results and equipment defect information in real time. With this analysis system, it can quickly provide information what user want and assistance in developing high quality radar.

• Soft Computing and Machine Intelligence
• /
• v.1 no.1
• /
• pp.1-10
• /
• 2021

Analysis and Tracking of bug reports is a challenging field in software repositories mining. It is one of the fundamental ways to explores a large amount of data acquired from defect tracking systems to discover patterns and valuable knowledge about the process of bug triaging. Furthermore, bug data is publically accessible and available of the following systems, such as Bugzilla and JIRA. Moreover, with robust machine learning (ML) techniques, it is quite possible to process and analyze a massive amount of data for extracting underlying patterns, knowledge, and insights. Therefore, it is an interesting area to propose innovative and robust solutions to analyze and track bug reports originating from different open source projects, including Mozilla and Eclipse. This research study presents an ML-based classification model to analyze and track bug defects for enhancing software engineering management (SEM) processes. In this work, Artificial Neural Network (ANN) and Naive Bayesian (NB) classifiers are implemented using open-source bug datasets, such as Mozilla and Eclipse. Furthermore, different evaluation measures are employed to analyze and evaluate the experimental results. Moreover, a comparative analysis is given to compare the experimental results of ANN with NB. The experimental results indicate that the ANN achieved high accuracy compared to the NB. The proposed research study will enhance SEM processes and contribute to the body of knowledge of the data mining field.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.339-339
• /
• 2000

In this parer, a method of measuring the size of defects on the wall and restructing the defect image of 3-dimension is developed based on the tracking algorithm of a camera position which uses the inclination angle of line slit beam for overcoming the difficulty of the corresponding problem identifying the image point in the both image. In the experiments, an algorithm for estimating the horizontal angle of CCD camera is presented and validated by applying it to the measurement of area and length under the variations of both the distance and the angle of CCD camera. And its performance is compared to that of the rotating and mapping method of image which has the Euclidian distance.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2004.10a
• /
• pp.457-464
• /
• 2004

소프트웨어의 품질을 향상시키기 위해 결함을 찾고 시정하는 것을 통제하는데 가장 중요한 요소가 바로 오류/장애/실패(통칭하여 결함(defects)를 효과적으로 추적하는 것이며, 결함을 추적하기 위해서는 효과적인 결함 추적시스템(Defect Tracking System)의 도입이 필요하다. 기존의 결함 추적 시스템은 고객/사용자로부터의 문제보고, 테스팅 기간 중의 결함보고, 변경관리 기능 등을 통합적으로 제공하고 있지 못하다는 점과 테스팅을 포함한 개발과정의 정량적 통제를 위한 데이터를 효과적으로 축적 제공하지 못하고, 더욱이 결함의 근본적인 원인을 찾아 해결할 수 있도록 하기 위한 정보를 효과적으로 제공하지 못하고 있는 문제가 있다. 본 논문에서는 이러한 기존의 결함 추적 시스템의 문제점을 해결하고자 설계/구축되어 현재 사내에서 활용되고 있는 결함관리 시스템인 Promise System을 소개하고자 한다. Promise 시스템은 고객의 불만 및 요구사항, 인스펙션 및 테스팅 시의 결함 및 요구사항에 대하여 각 담당자별로 업무를 할당, 추적할 수 있게 하고, 결함 및 요구사항에 관한 각종 상태정보와 통계 정보를 제공하여, 각 개발 및 테스팅 단계별로 결함 제거 목표의 수립, 정량적 통제, 결함 원인 분석을 통한 프로세스 개선 등을 지원하는 시스템이다.