• 제목/요약/키워드: structure detection

검색결과 2,044건 처리시간 0.03초

OFDM-기반 WPAN 시스템을 위한 패킷 검출 및 반송파 주파수 옵셋 추정/보정 구조 설계 및 분석 (Packet Detection and Frequency Offset Estimation/Correction Architecture Design and Analysis for OFDM-based WPAN Systems)

  • 백승호;이한호
    • 대한전자공학회논문지SD
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    • 제49권7호
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    • pp.30-38
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    • 2012
  • 본 논문은 mmWave OFDM-기반 WPAN 시스템을 위한 패킷 검출과 주파수 옵셋 추정 및 보정 구조를 제안하고 성능 분석 결과를 보여준다. 패킷 검출 블록은 반복된 훈련 심볼의 자기상관 관계를 이용하고 상관된 값이 일정 문턱 값을 넘을 때 패킷 시작점을 검출하는데 사용된다. 적용한 자기상관 알고리즘 구조는 기존의 패킷검출에 사용한 알고리즘에 비해 간단하게 하드웨어를 구현 할 수 있다. 주파수 옵셋 추정 구조는 기존구조와는 다른 위상 천이 처리 블록, 하드웨어 사이즈를 줄여주는 내부비트 줄임 블록 및 look-up table의 사이즈를 줄인 주파수 옵셋 조정 블록을 설계하였다. 추정된 주파수 옵셋 값은 설계한 보정 블록을 통해 수신 신호를 보정함으로써 주파수 옵셋에 대한 영향을 줄일 수 있다. 설계 검증툴을 이용한 성능 분석 결과 제안된 구조는 하드웨어 구현복잡도가 감소함을 보여 주었고 기존구조에 비하여 게이트수가 감소함을 보였다. 따라서 제안된 구조는 OFDM-기반 WPAN 시스템의 초기 동기화 과정에 적용 될 수 있고 고속 저전력 WPAN칩에 사용 될 수 있다.

Change Detection 기법을 이용한 구조물 안전진단측량 (Safety Inspection Surveying using Change Detection Technique)

  • 최철웅;곽재하;강인준
    • 대한공간정보학회지
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    • 제3권2호
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    • pp.151-158
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    • 1995
  • Change detection기법은 영상에서 차이를 알아내기 위하여 가장 많이 사용되는 방법이며 다양한 영상환경에 사용된다. 수치지형모델과 수치영상은 같은 수치격자데이타 구조를 가지므로 Change detection기법을 수치지형모델에 적용할 측량결과의 표고데이타를 불규칙삼각형(TIN)으로부터 격자구조로 변환하고 수치지형모델화하여 구조물의 변형지점을 찾는데 사용함으로 많은 소모성 자재와 인력을 줄일 수 있었다. 그 결과를 가시화하여 건물의 변형이 발생한 지점과 변형향을 수치적으로 나타낼 수 있었다.

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Damage detection of subway tunnel lining through statistical pattern recognition

  • Yu, Hong;Zhu, Hong P.;Weng, Shun;Gao, Fei;Luo, Hui;Ai, De M.
    • Structural Monitoring and Maintenance
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    • 제5권2호
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    • pp.231-242
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    • 2018
  • Subway tunnel structure has been rapidly developed in many cities for its strong transport capacity. The model-based damage detection of subway tunnel structure is usually difficult due to the complex modeling of soil-structure interaction, the indetermination of boundary and so on. This paper proposes a new data-based method for the damage detection of subway tunnel structure. The root mean square acceleration and cross correlation function are used to derive a statistical pattern recognition algorithm for damage detection. A damage sensitive feature is proposed based on the root mean square deviations of the cross correlation functions. X-bar control charts are utilized to monitor the variation of the damage sensitive features before and after damage. The proposed algorithm is validated by the experiment of a full-scale two-rings subway tunnel lining, and damages are simulated by loosening the connection bolts of the rings. The results verify that root mean square deviation is sensitive to bolt loosening in the tunnel lining and X-bar control charts are feasible to be used in damage detection. The proposed data-based damage detection method is applicable to the online structural health monitoring system of subway tunnel lining.

동적응답신호를 이용한 전단형 건물의 손상추정 (Damage Detection of Shear Building Structures Using Dynamic Response)

  • 유석형
    • 한국구조물진단유지관리공학회 논문집
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    • 제18권3호
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    • pp.101-107
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    • 2014
  • 구조물의 손상 추정은 동적응답신호로부터 고유주기와 모드형상을 구한 후 이를 역해석하여 손상위치와 손상정도를 파악함으로써 이루어 진다. 건축구조물의 경우 토목구조물에 비하여 구조형식이 복잡하고 비구조요소 및 노이즈 등의 영향으로 인하여 구조물 판별에 어려움이 있다. 동적응답신호를 이용한 건물의 손상추정에 관한 최근의 연구들은 손상추정을 위하여 민감도 또는 추정치 등 간접적 지표를 사용하고 있으나, 좀 더 합리적이고 명확한 손상추정을 위하여 운동방정식으로부터 직접 유도된 변수를 손상지수로 활용할 필요가 있을 것으로 판단된다. 따라서 본 연구에서는 전단형 건물의 운동방정식으로부터 직접 유도된 층강성 감소비를 손상지수로 하는 손상추정 방법을 제안하였다. 제안된 손상지수는 손상 전 모드형상과 손상 전 후 고유진동수 차이를 알면 구할 수 있다. 제안된 손상 추정방법을 수치해석예제에 적용한 결과 손상이 발생한 층에서 층강성 변화율이 (-)부호를 나타내었으며, 크기가 다른 층에 비하여 15배 정도 크게 나타나 전단형 건물의 손상 추정지수로서 활용될 수 있을 것으로 판단된다.

Real-time structural damage detection using wireless sensing and monitoring system

  • Lu, Kung-Chun;Loh, Chin-Hsiung;Yang, Yuan-Sen;Lynch, Jerome P.;Law, K.H.
    • Smart Structures and Systems
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    • 제4권6호
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    • pp.759-777
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    • 2008
  • A wireless sensing system is designed for application to structural monitoring and damage detection applications. Embedded in the wireless monitoring module is a two-tier prediction model, the auto-regressive (AR) and the autoregressive model with exogenous inputs (ARX), used to obtain damage sensitive features of a structure. To validate the performance of the proposed wireless monitoring and damage detection system, two near full scale single-story RC-frames, with and without brick wall system, are instrumented with the wireless monitoring system for real time damage detection during shaking table tests. White noise and seismic ground motion records are applied to the base of the structure using a shaking table. Pattern classification methods are then adopted to classify the structure as damaged or undamaged using time series coefficients as entities of a damage-sensitive feature vector. The demonstration of the damage detection methodology is shown to be capable of identifying damage using a wireless structural monitoring system. The accuracy and sensitivity of the MEMS-based wireless sensors employed are also verified through comparison to data recorded using a traditional wired monitoring system.

딥러닝 기반 교량 손상추정을 위한 Generative Adversarial Network를 이용한 가속도 데이터 생성 모델 (Generative Model of Acceleration Data for Deep Learning-based Damage Detection for Bridges Using Generative Adversarial Network)

  • 이강혁;신도형
    • 한국BIM학회 논문집
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    • 제9권1호
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    • pp.42-51
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    • 2019
  • Maintenance of aging structures has attracted societal attention. Maintenance of the aging structure can be efficiently performed with a digital twin. In order to maintain the structure based on the digital twin, it is required to accurately detect the damage of the structure. Meanwhile, deep learning-based damage detection approaches have shown good performance for detecting damage of structures. However, in order to develop such deep learning-based damage detection approaches, it is necessary to use a large number of data before and after damage, but there is a problem that the amount of data before and after the damage is unbalanced in reality. In order to solve this problem, this study proposed a method based on Generative adversarial network, one of Generative Model, for generating acceleration data usually used for damage detection approaches. As results, it is confirmed that the acceleration data generated by the GAN has a very similar pattern to the acceleration generated by the simulation with structural analysis software. These results show that not only the pattern of the macroscopic data but also the frequency domain of the acceleration data can be reproduced. Therefore, these findings show that the GAN model can analyze complex acceleration data on its own, and it is thought that this data can help training of the deep learning-based damage detection approaches.

항만 자동화를 위한 AGV 시스템의 장애물 감지 시스템의 구성에 관한 연구 (A Study on a Structure of Obstacle Detection System of AGV for Port Automation)

  • 박찬훈;최성락;박경택;김선호
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2000년도 추계학술대회논문집
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    • pp.227-234
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    • 2000
  • AGV is very proper equipment for Port Automation. AGV must have Obstacle Detection System(ODS) for port automation. Obstacle Detection System must have some functions. It must be able to classify some specified object from background data. And it must be able to track classified objects. Finally, ODS must determine its next action for safe cruise whether it must do emergency stop or it must speed down or it must change its track. For these functions, ODS can have many different structures. In this paper, we will propose one structure among some possible ones. Our ODS has been being developed using proposed structure since last year. In this paper, we will introduce our system which is under construction.

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응급의료정보시스템의 보호를 위한 보안 구조 (Security Structure for Protection of Emergency Medical Information System)

  • 신상열;양환석
    • 디지털산업정보학회논문지
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    • 제8권2호
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    • pp.59-65
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    • 2012
  • Emergency medical information center performs role of medical direction about disease consult and pre-hospital emergency handling scheme work to people. Emergency medical information system plays a major role to be decreased mortality and disability of emergency patient by providing information of medical institution especially when emergency patient has appeared. But, various attacks as a hacking have been happened in Emergency medical information system recently. In this paper, we proposed security structure which can protect the system securely by detecting attacks from outside effectively. Intrusion detection was performed using rule based detection technique according to protocol for every packet to detect attack and intrusion was reported to control center if intrusion was detected also. Intrusion detection was performed again using decision tree for packet which intrusion detection was not done. We experimented effectiveness using attacks as TCP-SYN, UDP flooding and ICMP flooding for proposed security structure in this paper.

APT 공격 탐지를 위한 공격 경로 및 의도 인지 시스템 (Attack Path and Intention Recognition System for detecting APT Attack)

  • 김남욱;엄정호
    • 디지털산업정보학회논문지
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    • 제16권1호
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    • pp.67-78
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    • 2020
  • Typical security solutions such as intrusion detection system are not suitable for detecting advanced persistent attack(APT), because they cannot draw the big picture from trivial events of security solutions. Researches on techniques for detecting multiple stage attacks by analyzing the correlations between security events or alerts are being actively conducted in academic field. However, these studies still use events from existing security system, and there is insufficient research on the structure of the entire security system suitable for advanced persistent attacks. In this paper, we propose an attack path and intention recognition system suitable for multiple stage attacks like advanced persistent attack detection. The proposed system defines the trace format and overall structure of the system that detects APT attacks based on the correlation and behavior analysis, and is designed with a structure of detection system using deep learning and big data technology, etc.

A $160{\times}120$ Light-Adaptive CMOS Vision Chip for Edge Detection Based on a Retinal Structure Using a Saturating Resistive Network

  • Kong, Jae-Sung;Kim, Sang-Heon;Sung, Dong-Kyu;Shin, Jang-Kyoo
    • ETRI Journal
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    • 제29권1호
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    • pp.59-69
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    • 2007
  • We designed and fabricated a vision chip for edge detection with a $160{\times}120$ pixel array by using 0.35 ${\mu}m$ standard complementary metal-oxide-semiconductor (CMOS) technology. The designed vision chip is based on a retinal structure with a resistive network to improve the speed of operation. To improve the quality of final edge images, we applied a saturating resistive circuit to the resistive network. The light-adaptation mechanism of the edge detection circuit was quantitatively analyzed using a simple model of the saturating resistive element. To verify improvement, we compared the simulation results of the proposed circuit to the results of previous circuits.

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