• 한국도로학회논문집
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• 제19권2호
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• pp.103-112
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• 2017

PURPOSES : In this study, field performance evaluation of crack treatment of pavement and the feasibility of surface treatment of pavement are presented. The performance and cost of preventive maintenance methods have been previously verified, and the methods are being used in many developed countries and cities. However, the performance and cost of the system have not been verified in domestic, field applications. Therefore, in order to improve performance, the field performance is evaluated, and a reasonable cost is proposed. METHODS : Visual Inspection was conducted to evaluate the field application and performance of the preventive maintenance method. In addition, the PCI index was calculated from the results of visual inspection of the application area of the surface treatment method, and the performance life of each method was predicted. For the economic evaluation, life cycle cost analysis was performed using the life cycle cost analysis program. RESULTS :In order to evaluate and quantify the field performance of crack repair material, the residue condition of the pavement surface after crack treatment, rather than the performance of the material, is evaluated. In addition, the crack resistance and performance life of surface treatment methods are evaluated. The cost of currently available treatment methods are compared to the common pavement cut and overlay method, and it is determined that the preventive method is not economical based on life cycle cost analysis. CONCLUSIONS :Because of the characteristics of cracking, it is necessary to conduct the evaluation of currently applied methods and the analysis of the cause of damage, by visual inspection. Moreover, in order to evaluate the performance and economic suitability of the currently applied surface treatment methods, it is necessary to acquire information on application sections by monitoring their long-term conditions and performance.

• 한국산학기술학회논문지
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• 제15권6호
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• pp.3416-3422
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• 2014

쇼크 업쇼바의 로드는 피스톤부 중심에 위치하여 왕복운동을 담당하는 부분으로 표면의 불량(찍힘)이 있을 경우 감쇠력에 대한 차이로 제품 성능을 제대로 발휘하는데 문제 발생의 요인이 되고 있다. 로드표면은 열처리 상태로 표면 광택으로 인하여 쉽게 불량이 표시되지 않으며, 작업자가 육안으로 로드의 이물질 및 찍힘, 기포 검사를 진행함으로써 눈의 피로도가 높아지고, 작업자 육안에 의존하기 때문에 제품의 검사 품질이 일정하지 않다. 본 연구에서는 제품의 원통 형상을 고려하여 라인스캔카메라를 이용한 머신비전 영상처리 기법으로 0.3mm이상의 표면의 불량을 검출하고, 검사단계에서 발생할 수 있는 표면 불량을 최소화하기 위한 전 공정 자동이송 및 양불 제품의 혼입을 방지하는 자동검사 시스템 개발에 대한 연구를 수행하였다. 표면검사 시스템 개발로 작업자의 육안 검사에 의존하고 있던 쇼크업쇼버 로드의 표면에 대한 정밀 검사시스템 구축으로 품질검사 기준을 확보하고 표준화된 검사로 신뢰도가 향상되었다.

• 한국구조물진단유지관리공학회 논문집
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• 제23권4호
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• pp.1-7
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• 2019

국가 주요 시설물의 안전점검 업무가 일원화됨에 따라 업무 효율성과 전문성 강화 등의 효과가 기대되고 있다. 세계적으로 시설물의 물리적 기능적 결함을 초기에 발견하는 외관조사의 중요성이 강조되고 있다. 이에 본 연구에서는 기존 외관조사 방법의 문제와 한계를 극복하기 위해 시설물 안전점검을 위한 E-PAD기반 상태평가 시스템을 개발하였다. 본 시스템은 시설개요, 작업목록, 외관조사, 결함표로 구성되어 있으며, 현장에서 외관조사망도를 다운받아 조사된 손상 및 정보를 입력하고, 평가 등급을 확인할 수 있다. 본 시스템의 검증을 위해 교량 10개소에 대한 외관조사 데이터를 입력하여 기존 안전등급을 비교하였다. 그 결과 시스템에서 산출된 안전등급과 기존 안전등급이 동일한 것으로 확인되었다. 또한 AHP기법을 통해 타당성 분석 결과 기존 방법 대비 기능 10%증가, 비용 36%감소, 가치 30%증가한 것으로 분석되었다. 따라서, 시설물 관리 수준 향상을 위해 체계적인 데이터 구축 및 정보 분석을 위한 시스템으로 기여할 것으로 기대된다.

• Corrosion Science and Technology
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• 제18권6호
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• pp.253-257
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• 2019

A deep learning based real-time painting surface inspection algorithm is proposed herein, designed for developing an autonomous inspection drone. The painting surface inspection is usually conducted manually. However, the manual inspection has a limitation in obtaining accurate data for correct judgement on the surface because of human error and deviation of individual inspection experiences. The best method to replace manual surface inspection is the vision-based inspection method with a camera, using various image processing algorithms. Nevertheless, the visual inspection is difficult to apply to surface inspection due to diverse appearances of material, hue, and lightning effects. To overcome technical limitations, a deep learning-based pattern recognition algorithm is proposed, which is specialized for painting surface inspections. The proposed algorithm functions in real time on the embedded board mounted on an autonomous inspection drone. The inspection results data are stored in the database and used for training the deep learning algorithm to improve performance. The various experiments for pre-inspection of painting processes are performed to verify real-time performance of the proposed deep learning algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.135-137
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• 2004

In this study we'll deal with the small-sized metalized film capacitors with large capacity which head have $5mm{\times}5mm{\times}2.5mm$ dimension. The lead wire is used to weld at both sides of capacitors. At that time the position gap between the welding machine and lead wire supplier would cause the welding error. Also, during the tapping processing of metalized film capacitors, the interval error among the capacitors, the length error of lead frame attached at the capacitors, and the straightness distortion of the lead frame could happen. As mentioned, four kinds of error parameters will be measured and analyzed by using the automatic visual inspection system that is implemented with CCD camera, optical parts, background lighting, and image processing algorithms. Finally we are able to achieve success rate above 99% to detect the welding faults of capacitors in the field test.

• 품질경영학회지
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• 제29권3호
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• pp.66-78
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• 2001

This paper deals with problem of determining process target value under automated visual inspection(AVI) system. Three independent error sources - digitizing error, illumination error, and positional error - which have a close relationship with the performance of the AVI system, are considered. Assuming that digitizing error is uniformly or normally distributed and illumination and positional errors are normally distributed, respectively, the distribution function for the error of measured lengths is derived when the length of a product is measured by the AVI system. Then, Optimal target values under two error models of AVI system are obtained by minimizing the total expected cost function which consists of give away, rework and penalty cost. To validate two process setting models, AVI system for drinks filling process is made up and test results are discussed.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2414-2417
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• 2005

Compact Camera Module(CCM) is widely used in PDA, Celluar phone and PC web camera. With the greatly increasing use for mobile applications, there has been a considerable demands for high speed production of CCM. The major burden of production of CCM is assembly of lens module onto CCD or CMOS packaged circuit board. After module is assembled, the CCM is inspected. In this paper, we developed the image capture board for CCM and the imaging processing algorithm to inspect the defects in captured image of assembled CCMs. The performances of the developed inspection system and its algorithm are tested on samples of 10000 CCMs. Experimental results reveal that the proposed system can focus the lens of CCM within 5s and we can recognize various types of defect of CCM modules with good accuracy and high speed.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 추계학술대회
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• pp.254-258
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• 2003

Electronic Speckle Pattern for quantitative evaluation of a impact defect inside of composite material plate are described. The impact on composite material makes inside delamination which is difficult to detect visual inspection and ultrasonic testing due to non-homeogenous structure. This paper proposes the quantitative evaluation technique of defects under real impact. Artificial defects are designed inside of composite plate for development of inspection technique and real defects under impact are inspected and compared with results of visual inspection.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
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• pp.959-962
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• 1988

This paper describes an automatic visual inspection system for fabric defects based on pattern recognition techniques. The inspection for fabric defects can be separated into three sequences of operations which are the detection of fabric defects[1], the classification of figures of fabric defects, and the classification of fabric defects. Comparing projections of defect-detected images with the predefined complex, the classification accuracy of figures of fabric defects was found to be 95.3 percent. Employing the Bayes classifier using cluster shade in SGLDM and variance in decorrelation method as features, the classification accuracy of regional figure defects was found to be 82.4 percent. Finally, some experimental results for line and dispersed figures of fabric defects are included.

• 한국구조물진단유지관리공학회 논문집
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• 제1권1호
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• pp.53-64
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• 1997

Recently, safety evaluation of structures has received great concern in this country. One major problem in safety evaluation is that the results are often quite different depending upon evaluation authority. This is mainly due to arbitrary selection of various modification factors when employing allowable stress method for safety evaluation, The purpose of the present study is, therefore, to establish a rational method to determine the modification factors, especially the stress modification factor and the deterioration modification factor based on visual examination. It is thought that the proposed method yields a rational and consistent result for safety evaluation and may efficiently be used for realistic evaluation of load capacity of bridge structures.