• Steel and Composite Structures
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• 제24권4호
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• pp.391-397
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• 2017

With the increasing application of explosive composite structure in many engineering fields, its interface bonding state detection is more and more significant to avoid catastrophic accidents. However, this task still faces challenges due to the complexity of the bonding interface. In this paper, the concept of nonlinear output frequency response functions (NOFRFs) is introduced to detect the bonding state of explosive composite structure. The NOFRFs can describe the nonlinear characteristics of nonlinear vibrating system. Because of the presence of the bonding interface, explosive composite structure itself is a nonlinear system; when bonding interface of the structure is damaged, its dynamic characteristics show enhanced nonlinear characteristic. Therefore, the NOFRFs-based detection index is proposed as indicator to detect the bonding state of explosive composite pipes. The experimental results verify the effectiveness of the detection approach.

• 반도체디스플레이기술학회지
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• 제17권1호
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• pp.54-61
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• 2018

In this study, two aspects were analyzed about the robot for removal of explosive devices. First, the cost analyses were performed to provide a reasonable solution for the acquirement of the system. It is processed by an engineering estimate method and the process was consisted of two ways : a system development expense and a mass production unit price. In additions, the resultant cost analyses were compared between the cases excluding and including a mines detection system. As results, in the case of the acquirement of the robot system for removal of explosive devices, it is recommended that the performance by improving the mines detection ability should be considered preferentially rather than the cost because the material cost for the mines detection system is negligible compared to the whole system cost. Second, as a way for improving the system performance by the mine detection function, the carbon nanotube (CNT) based sensor technology was studied in terms of sensitivity and simple productivity with presenting its preliminary experimental results. The detection electrodes were formed by a photolithography method using a photosensitive CNT paste. As results, this method was shown as a scalable and expandable technology for the excellent mines detection sensors.

• 공업화학
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• 제30권4호
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• pp.399-407
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• 2019

국내외 테러에 대한 공포와 안보 환경에서 폭발물을 검출 기술 개발은 매우 중요한 문제이다. 특히, 최근 항공보안성능 인증제 실시에 따른 폭발물 탐지 기술의 국산화 기술에 있어서 관련 연구가 요구된다. 폭발물 검출 및 탐지 기술은 전통적인 화학분석법을 통하여 이루어지고 있으나 높은 민감도, 빠른 분석, 소형화, 휴대성 등을 위해서는 전기화학적 방법이 적합하다고 여겨진다. 전기화학적 폭발물 탐지 기술의 대부분은 미국, 중국, 이스라엘 등에서 주로 연구가 되고 있지만 국내에서는 아직 관련 연구가 미비한 실정이다. 본 총설에서는 해외에서 수행되고 있는 전기화학적 폭발물 탐지 기술의 원리와 연구 동향을 보고하고 앞으로 우리가 탐구해야 할 연구 방향을 제시하고자 한다.

• 융합보안논문지
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• 제18권1호
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• pp.157-166
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• 2018

이 연구는 세계적으로 국가뿐만 아니라 민간인들을 대상으로 폭발물 테러가 빈번히 발생하고 있는 시점에서 다양한 기계장치와 인력을 배치하여 폭발물 탐지를 실시하고 있으나 기계장치의 오류, 인간의 감지능력 한계로 인하여 완벽한 폭발물 테러 예방이 어려운 상황임에 주목하였다. 따라서 이 연구는 폭발물 탐지견 도수사들의 인식을 분석을 토대로 폭발물 탐지견 활용을 통해 다양한 형태의 폭발물 테러로부터 국가중요시설 및 대형민간 시설과 시설 이용자들의 안전을 도모하기 위해 폭발물 탐지견 활용의 필요성을 인식하고 현재 문제점으로 나타나고 있는 상황에 대하여 개선책을 제시하고자 하였다. 도출된 결과는 첫째, 국가중요시설 및 대형 민간시설에 대한 폭발물 탐지견 도입 의무사항을 법률제도로서 입법화하는 것이다. 둘째, 폭발물 탐지견의 탐지능력을 검증하기 위하여 폭발물 탐지견의 인증제도를 도입하는 것이다. 셋째, 폭발물 탐지견을 운용하는 전문 도수사 활성화를 위한 전문 인력 양성제도를 도입하는 것이다.

• Bulletin of the Korean Chemical Society
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• 제34권6호
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• pp.1668-1672
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• 2013

We developed a standoff Raman detection system for explosive molecules (EMs). Our system was composed of reflective telescope with 310 mm diameter lens, 532 nm pulse laser, and Intensified Charge-Coupled Device (ICCD) camera. In order to remove huge background noise coming from ambient light, laser pulses with nanosecond time width were fired to target sample and ICCD was gated to open only during the time when the scattered Raman signal from the sample arrived at ICCD camera. We performed standoff experiments with military EMs by putting the detector at 10, 20 and 30 m away from the source. The standoff results were compared with the confocal Raman results. Based on our standoff experiments, we were able to observe the peaks in the range of 1200 and $1600cm^{-1}$, where vibrational modes of nitro groups were appeared. The wave numbers and shapes of these peaks may serve as good references in detecting and identifying various EMs.

• Steel and Composite Structures
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• 제31권3호
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• pp.233-242
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• 2019

Early detection of damage bonding state such as insufficient bonding strength and interface partial contact defect for the explosive clad pipe is crucial in order to avoid sudden failure and even catastrophic accidents. A generalized and efficient model of the explosive clad pipe can reveal the relationship between bonding state and vibration characteristics, and provide foundations and priory knowledge for bonding state detection by signal processing technique. In this paper, the slender explosive clad pipe is regarded as two parallel elastic beams continuously joined by an elastic layer, and the elastic layer is capable to describe the non-uniform bonding state. By taking the characteristic beam modal functions as the admissible functions, the Rayleigh-Ritz method is employed to derive the dynamic model which enables one to consider inhomogeneous system and any boundary conditions. Then, the proposed model is validated by both numerical results and experiment. Parametric studies are carried out to investigate the effects of bonding strength and the length of partial contact defect on the natural frequency and forced response of the explosive clad pipe. A potential method for identifying the bonding quality of the explosive clad pipe is also discussed in this paper.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2001년도 춘계학술발표회요약집
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• pp.510.2-510
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• 2001

• 인터넷정보학회논문지
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• 제23권4호
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• pp.11-19
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• 2022

본 논문은 컨볼루션 신경망(CNN)을 이용하여 폭발물 성분의 용량별로 분류할 때의 성능을 평가하는 연구이다. 기존의 폭발물 분류 방식 중에 IMS 증기 탐지기 방식은 폭발물의 농도가 사용자가 장비에서 설정한 임계치를 넘어야만 폭발물의 존재 여부를 판단한다. IMS 증기 탐지기는 폭발물이 존재하더라도 임계치를 넘지 않는 양이면 폭발물이 존재하지 않는다고 판단하는 문제가 있다. 따라서 폭발물 성분의 농도가 임계치를 넘지 않는 양일 때에도 폭발물 성분을 검출하는 방안이 필요하다. 이에 따라 본 논문에서는 폭발물 시계열 데이터를 Gramian Angular Field(GAF) 알고리즘으로 이미지화를 진행한 후 이미지와 영상처리뿐만 아니라 시계열 데이터 처리에도 뛰어난 성능을 보이는 딥러닝 모델인 컨볼루션 신경망(CNN)으로 직접 label을 설정해서 지도학습을 진행한 결과 폭발물 성분의 농도가 임계치를 넘지 않는 양일 때에도 폭발물 성분이 존재한다고 판단함과 동시에 폭발물 성분의 종류와 폭발물 성분의 농도의 양을 같이 판단할 수 있는지 성능평가를 진행했다.

• 센서학회지
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• 제19권6호
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• pp.497-503
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• 2010

This paper reports a chemomechanical explosive sensor based on a thin polymer membrane. The sensor consists of thin parylene membrane and electrodes. Parylene membrane is functionalized with 4-mercaptophenol which interacts strongly with nitrotoluene based explosives. The membrane deflection caused by molecular interaction between the surface and explosives is monitored by capacitance between the membrane and the substrate. To measure the capacitance, electrodes are formed on the membrane and the substrate. While the previous cantilever system requires a bulky optical measuring system, this purely electric monitoring method offers a compact and effective system. Thus, this explosive sensor can be readily miniaturized and used in the field. The developed sensor can reliably detect dinitrotoluene and its limit of detection is evaluated as approximately 110 ppb.

• 분석과학
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• 제33권2호
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• pp.86-97
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• 2020

Reconstruction and separation of explosive-contaminated overlapping fingerprints constitutes an analytical challenge of high significance in forensic sciences. Laser-induced breakdown spectroscopy (LIBS) allows real-time chemical mapping by detecting the light emissions from laser-induced plasma and can offer powerful means of fingerprint classification based on the chemical components of the sample. During recent years LIBS has been studied one of the spectroscopic techniques with larger capability for forensic sciences. However, despite of the great sensitivity, LIBS suffers from a limited detection due to difficulties in reconstruction of overlapping fingerprints. Here, the authors propose a simple, yet effective, method of using chemical mapping to separate and reconstruct the explosive-contaminated, overlapping fingerprints. A Q-switched Nd:YAG laser system (1064 nm), which allows the laser beam diameter and the area of the ablated crater to be controlled, was used to analyze the chemical compositions of eight samples of explosive-contaminated fingerprints (featuring two sample explosive and four individuals) via the LIBS. Then, the chemical validations were further performed by applying the Raman spectroscopy. The results were subjected to principal component and partial least-squares multivariate analyses, and showed the classification of contaminated fingerprints at higher than 91% accuracy. Robustness and sensitivity tests indicate that the novel method used here is effective for separating and reconstructing the overlapping fingerprints with explosive trace.