• 한국정밀공학회지
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• 제20권2호
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• pp.146-153
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• 2003

Ultrasonic inspection of defects has been focused on the existence of defect in structural material and need has much time and expenses in inspecting all the coordinates (x, y) on material surface. Neural networks can have an application to coordinates (x, y) of defects by multi-point inspection method. Ultrasonic inspection modeling is optimized by neural networks Neural networks has trained training example of absolute and relative coordinate of defects, and defect pattern. This method can predict coordinates (x, y) of defects within engineering estimated mean error $\psi$.

• 대한전자공학회논문지SD
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• 제43권8호
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• pp.1-5
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• 2006

본 논문은 극자외선 리소그래피용 마스크의 결함을 극자외선을 이용하여 검출하는 방법과 기존의 가시광선을 이용하여 결함을 검출해 내는 시스템과 비교하고, 인위적으로 만들어진 결함을 이용하여 극자외선이 결함에 조사되었을 때의 반사되는 패턴을 분석하였다. 포커스된 극자외선을 래스터 스캔 방식으로 조사하면서 반사되는 극자외선의 세기를 비교함으로서 결함을 발견해 내는 시스템을 구축하였고, 이를 이용하여 기존의 가시광선을 이용하는 결함 검출 장비와 상관 실험을 진행하여 반사된 빛의 세기로 예측한 결함의 크기가 두 검출 방법 사이에 강한 상관관계를 가짐을 확인하였다. 또한, 인광판을 이용하여 극자외선이 결함에 조사되어 반사되는 패턴을 영상화하여 크기별, 결함의 종류별로 다른 프린지 패턴을 가지는 것을 확인하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.946-949
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• 2005

This paper deals with the algorithm development that inspects defects such as Bright Defect Dots, Dark Defect Dots, and Line Defect caused by the process of LCD(Liquid Crystal Display). While most of LCD production process is automated, the inspection of LCD panel and its appearance depends on manual process. So, the quality of the inspection is affected by the condition of worker. Especially, the more LCD size increases, the more the worker feels fatigued, which causes the probability of miss judgement. So, the automated inspection is required to manage the consistent quality of the product and reduce the production costs. In this paper, to solve these problems, we developed the imaging processing algorithm to inspect the defects in captured image of LCD. Experimental results reveal that we can recognize various types of defect of LCD with good accuracy and high speed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1240-1242
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• 1996

In a still mill, the effective surface defect inspection algorithm is necessary. For this purpose, this paper proposed the preprocessing algorithm for surface defect inspection of cold mill strip. This consists of live steps. They are edge detection, binarizing, noise deletion, combining of fragmented defect and selecting the largest defect. Especially, binarizing is a critical problem. Bemuse the performance of the preprocessing is largely depend on the binarized image. So, we develope the adaptive thresholding method, which is multilevel thresholding. The thresholding value is varied according to the mean graylevel value of each test image. To investigate the performance of the proposed algorithm, we classified the detected defect using neural network. The test image is 20 defect images captured at German Sick Co. This algorithm is proved to have good property in cold mill strip surface inspection.

• 한국건축시공학회지
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• 제15권5호
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• pp.491-500
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• 2015

본 연구에서는 공동주택에서 건설 공사비 증가의 원인이 되는 하자에 대하여 건설업체의 공급자 중심이 아닌, 소비자가 법적인 하자보수 책임기간 만기를 앞두고 안전진단 전문기관에 의뢰하여 얻은 하자진단 결과보고서 자료를 근거로 공종별 하자실태를 조사하였다. 또한, 보수비용적 측면에서 세부요인을 분석하여, 시공단계에서의 품질향상과 하자분쟁 해결의 객관적이며 기초적인 자료를 제시하였다.

• 한국정밀공학회지
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• 제21권12호
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• pp.92-99
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• 2004

The formation degree of sustain (ITO pattern) decides quality of PDP (Plasma Display Panel). For this reason, it makes efforts in searching defects more than 30 un as 100%. Now, the existing inspection is dependent upon naked eye or microscope in off-line PDP manufacturing process. In this study developed prototype inspection system of PDP 170 glass is based on line-scan mechanism. Developed system creates information that detects and sorts kinds of defect automatically. Designed inspection technology adopts multi-vision method by slip-beam formation for the minimum of inspection time and detection algorithm is embodied in detection ability of developed system. Designed algorithm had to make good use of kernel matrix that draws up an approach to geometry. A characteristic of defects, as pin hole, substance, protrusion, are extracted from blob analysis method. Defects, as open, short, spots and et al, are distinguished by line type inspection algorithm. In experiment, we could have ensured ability of inspection that can be detected with reliability of up to 95% in about 60 seconds.

• 한국건설관리학회논문집
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• 제6권1호
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• pp.140-150
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• 2005

최근 공동주택의 마감자재가 고급화, 다양화되면서 품질만족에 대한 고객의 욕구가 과거 그 어느 때 보다도 증대되고 있으며 건설업체 또한 자사의 신인도 및 브랜드 가치의 상승을 위해 정밀시공을 통한 품질확보에 많은 노력을 기울이고 있다. 그러나 국내 공동주택 현장의 품질점검 및 하자관리는 현장관리 인원의 부족, 과다한 문서 발생, 업무 절차의 복잡성 및 관련주체간의 비효율적인 의사소통으로 품질점검에 따른 시설물의 이력관리 및 하자관리가 신속히 이루어지지 못하고 있는 실정이다. 따라서 본 연구의 목적은 이러한 품질점검 및 하자관리의 문제점을 해결하고자 PDA 및 웹을 활용하여 공동주택의 품질점검 및 하자관리에 대한 정보를 실시간으로 수집하고 이를 통해 관련 주체간의 효율적인 업무처리와 세대별 이력관리를 지원할 수 있도록 하는 공동주택 품질점검 및 하자관리 시스템을 구현하는 것이다. 본 연구에서 제시된 품질점검 및 하자 관리 시스템의 활용은 기존의 수작업에 의한 업무 절차를 간소화하고 관련 조직간의 원활한 의사소통과 시설물의 하자 관련 이력 데이터를 구축케 함으로써 품질관리 관련 업무의 질적 향상을 도모하고 궁극적으로는 품질 향상을 통한 건설업체의 고객 만족도 및 신인도 제고에도 크게 기여할 수 있을 것으로 기대된다.

• 한국건축시공학회지
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• 제13권3호
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• pp.209-217
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• 2013

The execution of a construction project involves the engagement of many participants. Generally, the Authority uses CM to certify that the Work is built according to the contract documents. The CM work scope is expressed in the Construction Technology Management Act and its Regulation. The mandated and delegated CM services are limited to the construction period. If Contractor is required to repair a construction defect, the Contractor should bear the burden of the inspection service for the defect repair, because it is associated with him. Nevertheless, CM should submit a bond to provide the inspection and supervision service for the defect repair. These may result in conflict with each liability. Therefore, CM service in the law and regulation was investigated and analyzed in this study to classify the characteristics of CM contracts, and it was suggested that the CM liability for the inspection and supervision service for the defect repair should be reconsidered.

• International Journal of Internet, Broadcasting and Communication
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• 제14권3호
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• pp.149-154
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• 2022

In recent years, the application of deep learning method to computer vision has shown to achieve great performances. Thus, many research projects have also applied deep learning technology to railroad defect detection. In this paper, we have reviewed the researches that applied computer vision based deep learning method to railroad defect detection and inspection, and have discussed the current trend and the direction of those researches. Many research projects were targeted to operate automatically without visual inspection of human and to work in real-time. Therefore, methods to speed up the computation were also investigated. The reduction of the number of learning parameters was considered important to improve computation efficiency. In addition to computation speed issue, the problem of annotation was also discussed in some research projects. To alleviate the problem of time consuming annotation, some kinds of automatic segmentation of the railroad defect or self-supervised methods have been suggested.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2007년도 7th International Meeting on Information Display 제7권1호
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• pp.286-289
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• 2007

We have developed an automated circuit defect inspection and repair method that can be used to improve the yield ratio of TFT-LCD. The method focuses on correcting resist patterns after the development process to ensure shape regularity. We built a prototype system and confirmed that the method is valid.