• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.9
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• pp.1175-1182
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• 2013

The lock-in mode infrared thermography (IRT) technique has been developed to improve the detection capability of defects in materials with high thermal conductivity, and it has been shown to provide better detection capability than conventional active IRT. Therefore, to investigate the application of this technique to nuclear piping components, lock-in mode IRT tests were conducted on pipe specimens containing simulated wall-thinning defects. Phase images of the wall-thinning defects were obtained from the tests, and they were compared with thermal images obtained from conventional active IRT tests. It showed that the ability to size the detected wall-thinning defects in piping components was improved by using lock-in mode IRT. The improvement was especially apparent when detecting short and narrow defects and defects with slanted edges. However, the detection capability for shallow wall-thinning defects did not improve much when using lock-in mode IRT.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10c
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• pp.677-679
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• 2000

결함의 검출은 결함 허용 시스템의 결함 허용성과 신뢰도 분석에 있어서 기초가 된다. 결함 검출 기법들은 각기 다른 특성을 가지고 있어 결함의 종류에 따라 다른 검출 능력을 가지기 때문에 효율적으로 시스템의 신뢰도를 향상시키기 위해서는 결함의 종류에 따라 적절한 기법들을 선별하여 적용해야 할 필요가 있다. 하지만 기존의 연구에서는 결함 검출 기법들에 대해 비교 검토에 대한 연구가 미흡하다. 따라서 결함의 종류에 따른 결함 검출 기법들의 성능을 평가하기 위한 테스트베드가 요구된다. 본 논문에서는 결함 검출을 위해 사용되고 있는 기법들의 종류를 분류하고 특성을 서술한다. 그리고, 리눅스 환경에서 소프트웨어로 구현된 결함 삽입 도구를 이용하여 각 결함 검출 기법들의 성능을 비교하기 위한 테스트베드를 설계한다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.473-479
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• 2002

NHPP에 근거한 SRGM을 구성하는 새로운 안을 제시한다. 본 논문의 주요 초점은 소프트웨어 신뢰도모델링에서 효과적인 파라미터분해기법을 제공하는 것이다. 이는 테스트노력과 결함검출비를 동시에 고려하는 것이다. 일반적으로, 소프트웨어결함검출/제거메카니즘은 이전의 검출/제거결함과 테스트노력을 어떻게 활용하느냐에 달려있다. 실제 현장 연구로부터 우리는 테스트노력소모패턴을 추론하여 FDR의 경향을 예측할 수 있을 것으로 생각된다. 결함검출이 증가, 감소 및 일정한 것 등 광범위에 걸쳐서 나타나는 경향을 잡아내는 고유의 융통성을 가지는 하나의 시변수집합인 FDR모델에 근거한 테스트노력을 개발하였다. 이 스킴은 구조에 융통성이 있어서 여러 가지 테스트노력을 고려하여 광범위한 소프트웨어 개발 환경을 모델화할 수 있다 본 논문에서는 FDR을 기술하고, 관련된 테스트 행위를 이러한 새로운 모델링접근법에 연합시킬 수 있다. 우리의 모델과 그리고 이것과 관련된 파라미터 분해기법을 적용한 것을 여러 가지 소프트웨어 프로젝트에서 도출한 실제 데이터집합을 통하여 시연한다. 분석결과에 의하면 SRGM에 관한 테스트노력과 FDR을 결합하기 위한 제안된 구조가 상당히 정확한 예측능력을 보여주고 있으며, 실제 수명상황을 좀더 정대하게 설명해 준다. 이 기법은 광범위한 소프트웨어시스템에 쓰일 수 있다.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.6
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• pp.451-459
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• 2016

Crack detection on panels during manufacturing process is an important step for ensuring the product quality. The accuracy and efficiency of traditional crack detection methods, which are performed by eye inspection, are dependent on human inspectors. Therefore, implementation of an on-line and precise crack detection is required during the panel pressing process. In this paper, a regular CCTV camera system is utilized to obtain images of panel products and an image process based crack detection technique is developed. This technique uses a comparison between the base image and a test image using an amplitude mapping of the local image. Experiments are performed in the laboratory and in the actual manufacturing lines to evaluate the performance of the developed technique. Experimental results indicate that the proposed technique could be used to effectively detect a crack on panels with high speed.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.13-18
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• 2004

It is important to estimate the distribution of intensity of a magnetic field for application of magnetic method to industrial nondestructive evaluation. Magnetic camera provides the distribution of a quantitative magnetic field with homogeneous lift-off and same spatial resolution. Leakage magnetic flux near the crack on the specimen could be amplified by 3-dimensional magnetic fluid and zoom in and out of measurement area. This study introduces the experimental consideration of the effects of lens for concentrating of magnetic flux. The experimental results showed that the magnetic fluid has sufficient lens effect for magnetic camera and effect of improvement in probability of detection.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.5
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• pp.341-348
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• 2015

Active infrared thermography methods have been known to possess good fault detection capabilities for the detection of defects in materials compared to the conventional passive thermal infrared imaging techniques. However, the reliability of the technique has been under scrutiny. This paper proposes the lock-in thermography technique for the detection and estimation of artificial subsurface defect size and depth with uncertainty measurement.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.345-348
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• 2005

소프트웨어 결함은 그것을 찾아내는 것도 힘들지만 정확한 해법을 찾는 것도 쉽지 않을 뿐더러, 또 테스트자의 능력 여하에 따라 수정중에 새로운 결함이 도입될 수도 있기 때문에 검출된 결함이 완벽하게 제거되기는 쉽지 않다. 따라서, 결함 제거 효율은 개발중인 소프트웨어의 신뢰도 성장이나 테스트 및 수정비용에 영향을 크게 미친다. 이는 소프트웨어 개발의 모든 과정에서 매우 유용한 척도로서 개발자가 디버깅 효율을 평가하는데 크게 도움이 될 뿐더러, 추가로 소요되는 작업량을 예측할 수 있게 해준다. 그러므로 개발 소프트웨어의 신뢰도와 비용면에서 불완전 디버깅의 영향을 연구하는 것은 매우 중요하다고 할 수 있으며, 이는 최적 인도 시각이나 운영 예산에도 영향을 줄 수 있다. 본 논문에서는 개발중인 소프트웨어를 대상으로 하여 디버깅이 완전하지 않으며, 이 때문에 디버깅 중 새로운 결함이 도입될 수도 있다는 제안하에 보편적으로 사용되는 신뢰도 모델을 대상으로 불완전 디버깅 범위로까지 소프트웨어의 신뢰도와 비용 문제를 확장하여 연구한다.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.3
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• pp.45-50
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• 1998

This paper presents experimental results on the application of very low frequency(VLF) voltage to replace conventional DC test as an after laying test for underground distribution cables. We carried out several tests to prove defects detecting ability of VLF test on the 5m length real cables having knife-cut or needle type defects which is made in our La.. Through this experiment we proved it is very difficult to initiate electrical tree from the defects inside of the cable insulation but once the electrical tree is initiated it grows very fast and VLF does not make new defects and expand the defect. Therefore VLF test equipment for quality inspection test of manufacture is more effective than field application for underground distribution cables.

• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.3
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• pp.162-173
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• 1997

Automatic on-line surface inspection systems have been applied for monitoring a quality of steel strip surfaces. One of the important issues in this application is the performance of on-line defect classifiers. Rule-based classification table methods which are conventionally used for this purpose have been suffered from their low performances. In this work, probabilistic neural networks and the enhanced classification tables which are newly proposed here are applied as alternative on-line classifiers to identify types of surface defects on cold rolled strips. Probabilistic neural networks have shown very excellent performance for classification of surface defects.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1177-1185
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• 2022

The water and sewage system is an infrastructure that provides safe and clean water to people. In particular, since the water and sewage pipelines are buried underground, it is very difficult to detect system defects. For this reason, the diagnosis of pipelines is limited to post-defect detection, such as system diagnosis based on the images taken after taking pictures and videos with cameras and drones inside the pipelines. Therefore, real-time detection technology of pipelines is required. Recently, pipeline diagnosis technology using advanced equipment and artificial intelligence techniques is being developed, but AI-based defect detection technology requires a variety of learning data because the types and numbers of defect data affect the detection performance. Therefore, in this study, various defect scenarios are implemented using 3D printing model to improve the detection performance when detecting defects in pipelines. Afterwards, the collected images are performed to pre-processing such as classification according to the degree of risk and labeling of objects, and real-time defect detection is performed. The proposed technique can provide real-time feedback in the pipeline defect detection process, and it would be minimizing the possibility of missing diagnoses and improve the existing water and sewerage pipe diagnosis processing capability.