• Smart Structures and Systems
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• 제13권6호
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• pp.901-925
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• 2014

The reliability of a Bridge management System depends on the quality of visual inspection and the reliable estimation of bridge condition rating. However, the current practices of visual inspection have been identified with several limitations, such as: they are time-consuming, provide incomplete information, and their reliance on inspectors' experience. To overcome such limitations, this paper presents an approach of automating the prediction of condition rating for bridges based on digital image analysis. The proposed methodology encompasses image acquisition, development of 3D visualization model, image processing, and condition rating model. Under this method, scaling defect in concrete bridge components is considered as a candidate defect and the guidelines in the Ontario Structure Inspection Manual (OSIM) have been adopted for developing and testing the proposed method. The automated algorithms for scaling depth prediction and mapping of condition ratings are based on training of back propagation neural networks. The result of developed models showed better prediction capability of condition rating over the existing methods such as, Naïve Bayes Classifiers and Bagged Decision Tree.

• Journal of Animal Science and Technology
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• 제64권1호
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• pp.155-165
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• 2022

As pork consumption increases, rapid and accurate determination of porcine carcass grades at abattoirs has become important. Non-destructive, automated inspection methods have improved slaughter efficiency in abattoirs. Furthermore, the development of a calibration equation suitable for non-destructive inspection of domestic pig breeds may lead to rapid determination of pig carcass and more objective pork grading judgement. In order to increase the efficiency of pig slaughter, the correct estimation of the automated-method that can accommodate the existing pig carcass judgement should be made. In this study, the previously developed calibration equation was verified to confirm whether the estimated traits accord with the actual measured traits of pig carcass. A total of 1,069,019 pigs, to which the developed calibration equation, was applied were used in the study and the optimal estimated regression equation for actual measured two traits (backfat thickness and hot carcass weight) was proposed using the estimated traits. The accuracy of backfat thickness and hot carcass weight traits in the estimated regression models through stepwise regression analysis was 0.840 (R²) and 0.980 (R²), respectively. By comparing the actually measured traits with the estimated traits, we proposed optimal estimated regression equation for the two measured traits, which we expect will be a cornerstone for the Korean porcine carcass grading system.

• 전자공학회논문지SC
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• 제49권1호
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• pp.8-11
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• 2012

자동 결함 검사 시스템 (AVI - Automated Vision Inspection Systems)은 디지털 영상을 통하여 표면의 결함을 자동으로 검출해 주는 시스템이다. 일반적으로 AVI 시스템의 성능은 한도 결함 검출력으로 판별한다. 한도 결함이란 결함 신호가 배경신호와 매우 유사하여 명확히 결함을 검출하기 어렵다. 본 논문에서는 신호대잡음비 (SNR - Signal to Noise Ratio)를 개선할 수 있는 전처리 기법을 제안하였다. 제안된 기법은 인간 시각 시스템 (HVS - Hunman Visual System) 원리를 기반으로 하였으며 이를 RLC (Run Length Code)로 구현하였다. 실험결과 제안된 전처리 기법은 한도 결함 영상에 대해 SNR이 두 배 이상 개선되는 효과를 보였으며 이를 이용하면 AVI 시스템의 검출성능 향상을 기대할 수 있다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.389-390
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• 2006

The goal of this paper is automation of a remocon inspection process using machine vision system. This system prevents error that is occurred by physical and spirit condition of human. Also this system has been developed to raise the reliability of remocon inspection. This system has been developed only using PC, CCD Camera and Visual C++ for universal workplaces. The performance of this system is an accuracy improvement of $2{\sim}3[%]$ and a processing time reduction of about 100[ms] against existing pattern matching method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.668-670
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• 1999

We have developed a automatic surface inspection system for cold Rolled strips in steel making process for several years. We have experienced the various kinds of surface inspection systems, including linear CCD camera type and the laser type inspection system which was installed in cold rolled strips production lines. But, we did not satisfied with these inspection systems owing to insufficient detection and classification rate, real time processing performance and limited line speed of real production lines. In order to increase detection and computing power, we have used the Dark Field illumination with Infra_Red LED, Bright Field illumination with Xenon Lamp, Parallel Computing Processor with Area typed CCD camera and full software based image processing technique for the ease up_grading and maintenance. In this paper, we introduced the automatic inspection system and real time image processing technique using the Object Detection, Defect Detection, Classification algorithms. As a result of experiment, under the situation of the high speed processed line(max 1000 meter per minute) defect detection is above 90% for all occurred defects in real line, defect name classification rate is about 80% for most frequently occurred 8 defect, and defect grade classification rate is 84% for name classified defect.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2008년도 정기 학술대회
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• pp.178-183
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• 2008

A robot crane truck is being developed by the Bridge Inspection Robot Development Interface(BRIDI) for an automated and/or teleoperated bridge inspection. At the end of the telescoping boom allows the operator to scan the bridge structure under the deck trough the camera. Boom vibration induced by wind and deck movement can cause serious problems in this scanning system. This paper presents a control system to mitigate such vibration of the robot boom In the proposed control system an actuator is installed at the end of the working boom. This control system is studied using a mathematical model analysis with LQ control algorithm and a scaled model test in the laboratory. The study indicates that the proposed system is efficient for the vibration control of the robot booms, thereby demonstrating its immediate applicability in the field.

• 반도체디스플레이기술학회지
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• 제11권2호
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• pp.45-51
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• 2012

Multilayer co-extrusion blown film construction is a popular technique for producing plastic films for various packaging industries. Automated detection of defective films can improve the quality of film production process. In this paper, we propose a film inspection system that can detect and classify film defects robustly. In our system, first, film images are acquired through a high speed line-scan camera under an appropriate lighting system. In order to detect and classify film defects, an inspection algorithm is developed. The algorithm divides the typical film defects into two groups: intensity-based and texture-based. Intensity-based defects are classified based on geometric features. Whereas, to classify texture-based defects, a texture analysis technique based on local binary pattern (LBP) is adopted. Experimental results revealed that our film inspection system is effective in detecting and classifying defects for the multilayer co-extrusion blown film construction line.

• 반도체디스플레이기술학회지
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• 제18권4호
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• pp.143-148
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• 2019

Numerous pipe lines can be found on various plant-based industrial sites. These pipelines should be periodically checked for defects. Most of these pipelines are internally inaccessible and difficult to visually inspect. Therefore, the inspection is being carried out with the help of non-contact inspection equipment such as ultrasonic flaw detection equipment. The use of ultrasonic flaw detection equipment can raise time and efficiency issues. In order to solve this problem, we will study the basic technology necessary for the development of automated inspection system equipped with ultrasonic measuring equipment and verify the validity through the fabrication of the demonstration device.

• 제어로봇시스템학회논문지
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• 제9권8호
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• pp.640-646
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• 2003

We presents an edge-based point correlation algorithm for fast and stable visual inspection system. Conventional algorithms based on NGC(normalized gray-level correlation) have to overcome some difficulties in applying automated inspection systems to real factory environment. First of all, NGC algorithms involve highly complex computation and thus require high performance hardware for realtime process. In addition, lighting condition in realistic factory environments is not stable and therefore intensity variation from uncontrolled lights gives many troubles for applying NGC directly as pattern matching algorithm. We propose an algorithm to solve these problems, using thinned and binarized edge data, which are obtained from the original image. A point correlation algorithm with the thinned edges is introduced with image pyramid technique to reduce the computational complexity. Matching edges instead of using original gray-level image pixels overcomes problems in NGC method and pyramid of edges also provides fast and stable processing. All proposed methods are proved by the experiments using real images.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.327-328
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• 2006

Recently, as the infocomindustry is developed, the semiconductor industry as well as the optical industry such as the optical communication and the optical instrument is developed rapidly. The transmission, storage and processing of information has been reaching an limit because amounts of information increase rapidly. The more quickly the optical communication is developed, the more sharply the demand of optical elements increase. The transport and inspection process is time consuming and the error rate is high, because this process are not automated in case of an optical lens. In this paper, the pick-up system that can hold optical elements and be transferred by the ultrasonic transport system is developed. The inspection system that distinguishes between the existence and the nonexistence of a defect is connected easily to pick-up system. The pick-up system separates the optical glass lens by results of the inspection. The automation program is developed by visual c++ programming.