• 한국건축시공학회지
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• 제21권6호
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• pp.665-676
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• 2021

노후 건축물의 수가 증가함에 따라, 건물의 안전진단, 유지 보수에 대한 중요성이 증가하고 있다. 기존 외관 조사는 점검자의 주관적인 판단이 수반되어 평가 결과가 다르고 객관성과 신뢰성이 떨어진다. 따라서 본 연구는 기존 연구를 통해 기실시된 외관 조사 및 상태 평가 프로세스의 한계를 제시하였으며, UAV, Laser Scanner를 통해 3D Point Cloud 데이터를 수집하였다. 또한, Reverse Engineering 기술을 이용하여 3D 모델을 생성한 후 객관적인 상태평가 데이터를 취득하였다. 이후 기존의 정밀검사 데이터와 정밀 안전진단 데이터를 활용하여 DNN 구조를 생성하고, 고정밀도 측정 장치를 이용하여 얻은 상태평가 데이터를 적용하여 객관적인 건물안전등급을 산출하였다. 자동화된 프로세스는 20개의 노후된 건축물에 적용되며 동일 면적 건축물 기준 수작업으로 실시되는 안전진단의 시간에 비해 약 50% 감소하였다. 이후 본 연구에서는 안전등급 결과값과 기존값을 비교하여 안전등급 산출과정의 정확성을 검증하고 약 90%의 높은 정확도를 가진 DNN을 구축하였다. 이는 향후 노후 건물의 안전등급 산정의 신뢰성이 향상되고 비용과 시간을 절약해 경제성이 향상될 것으로 기대된다.

• Journal of Computational Design and Engineering
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• 제2권1호
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• pp.55-66
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• 2015

To satisfy safety regulations of Economic Commission for Europe (ECE), the surface regions of automobile parts must have a sufficient degree of roundness if there is any chance that they could contact a sphere of 50.0 mm radius (exterior parts) or 82.5 mm radius (interior parts). In this paper, a new offset-based method is developed to automatically detect the possible sphere-contacting shape of such parts. A polyhedral model that precisely approximates the part shape is given as input, and the offset shape of the model is obtained as the Boolean union of the expanded shapes of all surface triangles. We adopt a triple-dexel representation of the 3D model to enable stable and precise Boolean union computations. To accelerate the dexel operations in these Boolean computations, a new parallel processing method with a pseudo-list structure and axis-aligned bounding box is developed. The possible sphere-contacting shape of the part surface is then extracted from the offset shape as a set of points or a set of polygons.

• 한국측량학회지
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• 제40권5호
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• pp.413-419
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• 2022

지하공간의 개발이 활발해짐에 따라 최근에는 지하와 관련된 안전사고가 자주발생하고 있다. 이와 관련하여 국토교통부에서는 『지하안전관리에 관한 특별법』(2018.01.01. 시행, 이하 지하안전법)을 시행하고 있다. 지하안전법의 핵심이 되는 내용 중에는 현재 우리나라에서 지하공간에 존재하는 지하시설물, 지하구조물, 지반의 지하정보를 3차원으로 가시화 할 수 있도록 지하공간통합지도를 구축하고 이를 활용하는 것을 포함하고 있다. 본 연구는 지하공간통합지도 중 3차원의 지하구조물 데이터를 대상으로 3차원 모델 생성 후 이를 빠르게 검수할 수 있는 프로그램을 개발하는 것을 목적으로 한다. 이를 위하여 우선 3차원 지하구조물 데이터를 생성하고 자동 검수하는 기술에 대하여 국내·외 현황을 조사하였다. 핵심이 되는 연구내용으로는 지하공간통합지도를 구축할 때 3차원 지하구조물의 검수기준에 따라 자동으로 3차원 모델 품질을 검수하는 프로그램을 개발하였다. 본 연구를 통하여 현재 수작업 방식으로 진행하고 있는 3차원 모델 검수과정을 98% 이상 자동화함으로써 지하공간통합지도 지하구조물의 3차원 모델의 품질향상을 도모할 수 있을 것으로 기대된다.

• 한국가스학회지
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• 제22권6호
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• pp.40-43
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• 2018

압력안전밸브의 열림고장과 닫힘고장은 서로 부분적으로 종속되어있다. 본 연구에서는 마르코프 프로세스 모델과 Weibull 분포 모델을 이용하여 두 가지 고장에 대한 신뢰성 모델을 구축하는 방법을 제안한다. 압력안전 밸브 모델은 알려진 열림고장 모델, 유도된 닫힘고장 모델, 최근 보고된 점검결과를 재현하는 동시고장 모델로부터 얻어진다. 제안된 방법은 부분적으로 종속된 다중 고장상태를 갖는 다양한 시스템의 정량적 위험성 평가로 확대 적용할 수 있을 것으로 기대된다.

• 시스템엔지니어링학술지
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• 제12권1호
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• pp.89-103
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• 2016

Due to safety of the plant, it became very clear the importance of study occurrence reactor coolant system (RCS) issues specially the primary water stress corrosion cracking (PWSCC). The Systems Engineering (SE) approach is characterized by the application of a structured engineering methodology for the design of a complex system or component. Robotic devices have been used for internal inspection, maintenance and performing remote welding and inspection in high-radiation areas. In this paper, PWSCC overview and inlay and over lay welding methodology introduced, concept of robotic device that can be inserted into the piping via Steam Generator (SG) main way to access to primary piping of pressurized water reactor (PWR) is developed based on SE methodology. A 3D model of the inspection system was developed along with the APR1400 (Advanced Power Reactor)reactor coolant systems (RCS) and internals with virtual 3D simulation of the operation for visualization to prove the validity of the concept.

• 한국가스학회지
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• 제23권1호
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• pp.62-69
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• 2019

울산, 여수 등 산업단지의 고압매설배관은 주변의 석유화학사의 원료 물질 및 스팀 등 유틸리티 지원을 위해 많은 배관이 매설되어 있음은 물론 독성, 가연성 불활성 가스 등이 고압으로 거미줄처럼 복잡하게 매설되어 공급되고 있다. 이에 산업단지배관과 도시가스 매설배관의 안전 관리 현황을 심층 비교 분석한 것을 바탕으로 타 공사에 의한 배관손상 영향인자인 굴착빈도, 굴착 깊이, 순찰 주기 등을 분석하고, 타 공사 위험감소 전략에 따른 위험변화 및 상관관계를 비교하여 산업단지 고압 매설배관에 대한 안전 점검 운영 모델을 제시한다.

• 한국해양공학회지
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• 제30권3호
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• pp.194-200
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• 2016

Recently, UUVs (unmanned underwater vehicles) have increasingly been applied in various science and engineering applications. In-water inspection, which used to be performed by human divers, is a potential application for UUVs. In particular, the operational safety and performance of in-water inspection missions can be greatly improved by using an underwater robotic vehicle. The capabilities of hovering maneuvers and automatic image mosaicking are essential for autonomous underwater visual inspection. This paper presents the development of a hover-capable autonomous underwater vehicle system for autonomous in-water inspection, which includes both a hardware platform and operational software algorithms. Some results from an experiment in a model basin are presented to demonstrate the feasibility of the developed system and algorithms.

• 한국안전학회지
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• 제33권6호
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• pp.37-41
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• 2018

Process safety technology has developed from qualitative methods such as HAZOP (hazard and operability study) to semi-quantitative methods such as LOPA (layer of protection analysis), and quantitative methods are actively studied these days. Quantitative risk assessment (QRA) is often based on fault tree analysis (FTA). FTA is efficient, but difficult to apply when failure events are not independent of each other. This problem can be avoided using a Markov process (MP). MP requires definition of all possible states, and thus, generally, is more complicated than FTA. A method is proposed in this work that uses an MP model and a Weibull distribution model in order to construct a reliability model for multiple dependent failures. As a case study, a pressure safety valve (PSV) is considered, for which there are three kinds of failure, i.e. open failure, close failure, and gas tight failure. According to recently reported inspection results, open failure and close failure are dependent on each other. A reliability model for a PSV group is proposed in this work that is to reproduce these results. It is expected that the application of the proposed method can be expanded to QRA of various systems that have partially dependent multiple failure states.

• 한국구조물진단유지관리공학회 논문집
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• 제6권3호
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• pp.97-102
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• 2002

Two dimensional Analysis has been applied to most of tunnel lining design in these days. Two dimensional analysis uses beam or curved beam element for finite element method. But because the behaviors of tunnel concrete lining structure is near to shell, it is required to model the tunnel lining as shell structure for safety design of tunnel lining structure. In this paper, two dimensional analysis by beam element and the three dimensional analysis by shell element of tunnel concrete lining are studied, in which 3 type of tunnel lining and lateral pressure factors are considered. As results of the study, three dimensional analyses of the behavior of tunnel concrete lining structure considering lateral pressure factor shows that the moment of three dimensional analysis is greater than those of two dimensional analysis. The results shows that three dimensional analysis is necessary for safety design of tunnel lining.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.87-95
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• 2020

Generally, occupational safety and particularly construction safety is an intricate phenomenon. Industry professionals have devoted vital attention to enforcing Occupational Safety and Health (OHS) from the last three decades to enhance safety management in construction. Despite the efforts of the safety professionals and government agencies, current safety management still relies on manual inspections which are infrequent, time-consuming and prone to error. Extensive research has been carried out to deal with high fatality rates confronting by the construction industry. Sensor systems, visualization-based technologies, and tracking techniques have been deployed by researchers in the last decade. Recently in the construction industry, computer vision has attracted significant attention worldwide. However, the literature revealed the narrow scope of the computer vision technology for safety management, hence, broad scope research for safety monitoring is desired to attain a complete automatic job site monitoring. With this regard, the development of a broader scope computer vision-based risk recognition system for correlation detection between the construction entities is inevitable. For this purpose, a detailed analysis has been conducted and related rules which depict the correlations (positive and negative) between the construction entities were extracted. Deep learning supported Mask R-CNN algorithm is applied to train the model. As proof of concept, a prototype is developed based on real scenarios. The proposed approach is expected to enhance the effectiveness of safety inspection and reduce the encountered burden on safety managers. It is anticipated that this approach may enable a reduction in injuries and fatalities by implementing the exact relevant safety rules and will contribute to enhance the overall safety management and monitoring performance.