• Title/Summary/Keyword: Defect Module Detection

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Nondestructive Detection of Defect in a Pipe Using Thermography

  • Choi, Hee-Seok;Joung, Ok-Jin;Kim, Young-Han
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1413-1416
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    • 2005
  • An infrared temperature sensor module developed for the detection of defects in a plate was modified to use in a cylinder. A set of optical fiber leads and a mechanism maintaining sensor-object distance constant were utilized for the modification of the IR sensor module. The detection performance was experimentally investigated, and the measured temperature was also compared with computed temperature distribution. The experimental outcome indicates that the detection of a simulated defect is readily available. The temperature distribution is better for defect detection than that with the previous device. In addition, the measured distribution is comparable to the calculated one using a heat conduction equation. The developed device of defect detection is suitable to be utilized in chemical processes where most of vessels and piping systems are in the shape of a cylinder.

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Development on the Process Control System for Full Gate Visual Test of LCD Manufacturing Process (LCD 생산공정의 전게이트 시각 검사를 위한 공정 제어장치 개발)

  • Park, Hyoung-Keun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.10 no.7
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    • pp.1725-1728
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    • 2009
  • This research developed process control device and FGV pattern generating device essential for full gate visual inspection to improve process so that defect detection capability may be maximized in specified environment. The devices developed in this research, which can be swiftly replaced in case loss or error occurs, are anticipated to improve module yield as well as maintain tact loss near '0'. In addition, as a result of mounting H/W and S/W system to control detailed operation sequence in production line and executing performance check and verification, detection rates were 98.1% and 99.1% respectively for pixel defect by tact and line defect, and yield of the entire module process including gate and visual level test increased up to 98.3%.

A Study of the Defect Detection Method of Vision Technology via Camera Image Analysis on 4-col 7-row LED Screen Module (4단 7열 LED 사이니지 전면부 설치형 카메라기반 불량 LED 소자 검출 Vision 기술에 관한 연구)

  • Park, Young ki;Im, Sang il;Jo, Ik hyeon;Cha, Jae sang
    • Journal of Korea Multimedia Society
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    • v.23 no.11
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    • pp.1383-1387
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    • 2020
  • Recently, a 4-col 7-row LED Screen that provides various information of major roads and local governments has been installed and operated. However, due to deterioration due to changes in temperature and humidity, deterioration due to static electricity, and mechanical stress, partial module failure of the display may occur, which is a major cause of missing information of vitally given to citizens. However, there have been frequent cases where the 4-col and 7-row LED Screen that have failed due to reasons such as installed location where the signboards are installed on the road and outdoor, the lack of monitoring means at all times, and the lack of manpower is often neglected for a long time. Following this flow, this paper proposes a method to detect defective modules by analyzing the images collected through the camera fixed to the front part of the LED display.

Linear System Depth Detection using Retro Reflector for Automatic Vision Inspection System (자동 표면 결함검사 시스템에서 Retro 광학계를 이용한 3D 깊이정보 측정방법)

  • Joo, Young Bok
    • Journal of the Semiconductor & Display Technology
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    • v.21 no.4
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    • pp.77-80
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    • 2022
  • Automatic Vision Inspection (AVI) systems automatically detect defect features and measure their sizes via camera vision. It has been populated because of the accuracy and consistency in terms of QC (Quality Control) of inspection processes. Also, it is important to predict the performance of an AVI to meet customer's specification in advance. AVI are usually suffered from false negative and positives. It can be overcome by providing extra information such as 3D depth information. Stereo vision processing has been popular for depth extraction of the 3D images from 2D images. However, stereo vision methods usually take long time to process. In this paper, retro optical system using reflectors is proposed and experimented to overcome the problem. The optical system extracts the depth without special SW processes. The vision sensor and optical components such as illumination and depth detecting module are integrated as a unit. The depth information can be extracted on real-time basis and utilized and can improve the performance of an AVI system.

Visual Inspection of Tube Internal

  • Choi, Young-Soo;Cho, Jai-Wan;Kim, Chang-Hoi;Seo, Yong-Chil;Kim, Seung-Ho
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.789-792
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    • 2003
  • Pipe inspection has a great importance to ensure safety for the nuclear power plant. In this paper, we designed visual inspection module for the tube internal, which diameter is 15${\sim}$20mm. And we made inspection module which consisted of CCD camera and light. And the relation between image and real world coordinate is established. Image processing is performed to calculate mapping parameter and analyze the size of defect. For the calculation of mapping parameter, experiment is performed using grid type test pattern. Acquired image is processed to extract image coordinate. Edge detection, thresholding, median filtering and morphology filtering is applied to extract grid pattern. Extracted image coordinate is used to calculate image to real world mapping. Lens distortion was considered and corrected to get exact data. Coordinate transformation data is provided for the users to recognize easily. Experiment was performed using grid type test pattern, we extracted lens distortion parameter and real coordinate of defect point. Radial distortion of lens was corrected but tangential distortion was not considered. As continuum to this study, the tangential distortion of lens is considered and improvement of analy zing technique for the tube internal be explored continuously.

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Hierarchical Flow-Based Anomaly Detection Model for Motor Gearbox Defect Detection

  • Younghwa Lee;Il-Sik Chang;Suseong Oh;Youngjin Nam;Youngteuk Chae;Geonyoung Choi;Gooman Park
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.6
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    • pp.1516-1529
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    • 2023
  • In this paper, a motor gearbox fault-detection system based on a hierarchical flow-based model is proposed. The proposed system is used for the anomaly detection of a motion sound-based actuator module. The proposed flow-based model, which is a generative model, learns by directly modeling a data distribution function. As the objective function is the maximum likelihood value of the input data, the training is stable and simple to use for anomaly detection. The operation sound of a car's side-view mirror motor is converted into a Mel-spectrogram image, consisting of a folding signal and an unfolding signal, and used as training data in this experiment. The proposed system is composed of an encoder and a decoder. The data extracted from the layer of the pretrained feature extractor are used as the decoder input data in the encoder. This information is used in the decoder by performing an interlayer cross-scale convolution operation. The experimental results indicate that the context information of various dimensions extracted from the interlayer hierarchical data improves the defect detection accuracy. This paper is notable because it uses acoustic data and a normalizing flow model to detect outliers based on the features of experimental data.

Fault Detection in Diecasting Process Based on Deep-Learning (다단계 딥러닝 기반 다이캐스팅 공정 불량 검출)

  • Jeongsu Lee;Youngsim, Choi
    • Journal of Korea Foundry Society
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    • v.42 no.6
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    • pp.369-376
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    • 2022
  • The die-casting process is an important process for various industries, but there are limitations in the profitability and productivity of related companies due to the high defect rate. In order to overcome this, this study has developed die-casting fault detection modules based on industrial AI technologies. The developed module is constructed from three-stage models depending on the characteristics of the dataset. The first-stage model conducts fault detection based on supervised learning from the dataset without labels. The second-stage model realizes one-class classification based on semi-supervised learning, where the dataset only has production success labels. The third-stage model corresponds to fault detection based on supervised learning, where the dataset includes a small amount of production failure cases. The developed fault detection module exhibited outstanding performance with roughly 96% accuracy for actual process data.

A Comparative Study on Similarity Measure Techniques for Cross-Project Defect Prediction (교차 프로젝트 결함 예측을 위한 유사도 측정 기법 비교 연구)

  • Ryu, Duksan;Baik, Jongmoon
    • KIPS Transactions on Software and Data Engineering
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    • v.7 no.6
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    • pp.205-220
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    • 2018
  • Software defect prediction is helpful for allocating valuable project resources effectively for software quality assurance activities thanks to focusing on the identified fault-prone modules. If historical data collected within a company is sufficient, a Within-Project Defect Prediction (WPDP) can be utilized for accurate fault-prone module prediction. In case a company does not maintain historical data, it may be helpful to build a classifier towards predicting comprehensible fault prediction based on Cross-Project Defect Prediction (CPDP). Since CPDP employs different project data collected from other organization to build a classifier, the main obstacle to build an accurate classifier is that distributions between source and target projects are not similar. To address the problem, because it is crucial to identify effective similarity measure techniques to obtain high performance for CPDP, In this paper, we aim to identify them. We compare various similarity measure techniques. The effectiveness of similarity weights calculated by those similarity measure techniques are evaluated. The results are verified using the statistical significance test and the effect size test. The results show k-Nearest Neighbor (k-NN), LOcal Correlation Integral (LOCI), and Range methods are the top three performers. The experimental results show that predictive performances using the three methods are comparable to those of WPDP.

Development of hyperspectral image-based detection module for internal defect inspection of 3D-IC semiconductor module (3D-IC 반도체 모듈의 내부결함 검사를 위한 초분광 영상기반 검출모듈 개발)

  • Hong, Suk-Ju;Lee, Ah-Yeong;Kim, Ghiseok
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 2017.04a
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    • pp.146-146
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    • 2017
  • 현대의 스마트폰 및 태블릿pc등을 가능하게 만든 집적 기술 중의 하나는 3차원 집적 회로(3D-IC)와 같은 패키징 기술이다. 이러한 첨단 3차원 집적 기술은 메모리집적을 통한 대용량 메모리 모듈 개발뿐만 아니라, 메모리와 프로세서의 집적, high-end FPGA, Back side imaging (BSI) 센서 모듈, MEMS 센서와 ASIC 집적, High Bright (HB) LED 모듈 등에 적용되고 있다. 3D-IC의 3차원 모듈 제작 시에는 기존에 발생하지 않았던 여러 가지 파괴 모드들이 발생하고 있는데 Thermal/Photonic Emission 장비 등 기존의 2차원 결함분리 (Fault Isolation) 기술로는 첨단의 3차원 적층 제품들에서 발생하는 불량을 비파괴적으로 혹은 3차원적으로 분리하는 것이 불가능하므로, 비파괴 3차원 결함 분리 기술은 향후 선행 제품 적기 개발에 매우 필수적인 기술이다. 본 연구는 3D-IC 반도체의 비파괴적 내부결함 검사를 위하여 가시광선-근적외선 대역(351nm~1770nm)의 InGaAs (Indium Galium Arsenide) 계열 영상검출기 (imaging detector)를 사용하여 분광 시스템 광학 설계를 통한 초분광 영상 기반 검출 모듈을 제작하였다. 제작된 초분광 영상 기반 검출 모듈을 이용하여 구리 회로 위에 실리콘 웨이퍼가 3단 적층 된 반도체 더미 샘플의 초분광 영상을 촬영하였으며, 촬영된 초분광 영상에 대하여 Chemometrics model 기반의 분석기술을 적용하여 실리콘 웨이퍼 내부의 집적 구조에 대한 검사가 가능함을 확인하였다.

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Modified LEACH Protocol improving the Time of Topology Reconfiguration in Container Environment (컨테이너 환경에서 토플로지 재구성 시간을 개선한 변형 LEACH 프로토콜)

  • Lee, Yang-Min;Yi, Ki-One;Kwark, Gwang-Hoon;Lee, Jae-Kee
    • The KIPS Transactions:PartC
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    • v.15C no.4
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    • pp.311-320
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    • 2008
  • In general, routing algorithms that were applied to ad-hoc networks are not suitable for the environment with many nodes over several thousands. To solve this problem, hierarchical management to these nodes and clustering-based protocols for the stable maintenance of topology are used. In this paper, we propose the clustering-based modified LEACH protocol that can applied to an environment which moves around metal containers within communication nodes. In proposed protocol, we implemented a module for detecting the movement of nodes on the clustering-based LEACH protocol and improved the defect of LEACH in an environment with movable nodes. And we showed the possibility of the effective communication by adjusting the configuration method of multi-hop. We also compared the proposed protocol with LEACH in four points of view, which are a gradual network composition time, a reconfiguration time of a topology, a success ratio of communication on an containers environment, and routing overheads. And to conclude, we verified that the proposed protocol is better than original LEACH protocol in the metal containers environment within communication of nodes.