• 제목/요약/키워드: Smart disaster prevention

검색결과 89건 처리시간 0.02초

Nonlinear damage detection using linear ARMA models with classification algorithms

  • Chen, Liujie;Yu, Ling;Fu, Jiyang;Ng, Ching-Tai
    • Smart Structures and Systems
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    • 제26권1호
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    • pp.23-33
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    • 2020
  • Majority of the damage in engineering structures is nonlinear. Damage sensitive features (DSFs) extracted by traditional methods from linear time series models cannot effectively handle nonlinearity induced by structural damage. A new DSF is proposed based on vector space cosine similarity (VSCS), which combines K-means cluster analysis and Bayesian discrimination to detect nonlinear structural damage. A reference autoregressive moving average (ARMA) model is built based on measured acceleration data. This study first considers an existing DSF, residual standard deviation (RSD). The DSF is further advanced using the VSCS, and then the advanced VSCS is classified using K-means cluster analysis and Bayes discriminant analysis, respectively. The performance of the proposed approach is then verified using experimental data from a three-story shear building structure, and compared with the results of existing RSD. It is demonstrated that combining the linear ARMA model and the advanced VSCS, with cluster analysis and Bayes discriminant analysis, respectively, is an effective approach for detection of nonlinear damage. This approach improves the reliability and accuracy of the nonlinear damage detection using the linear model and significantly reduces the computational cost. The results indicate that the proposed approach is potential to be a promising damage detection technique.

전기부하 패턴분류를 위한 신호처리 기법에 관한 연구 (A Study on the Signal Processing Techiques for Pattern Classification of Electrical Loads)

  • 임용배;김동우;진상민;조성원
    • 한국지능시스템학회논문지
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    • 제26권5호
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    • pp.409-415
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    • 2016
  • 최근 사물인터넷 기반의 재해예방 기술이 개발되고 있다. 본 논문에서는 사물인터넷기반의 공동주택용 자율전기안전관리 기술 개발을 위하여 부하 전류 파형을 FFT와 MFCC를 이용하여 신호변환 후 신경회로망 모델에 적용하여 정확도가 개선된 전기 부하 패턴분류 시스템을 제안한다. 오실로스코프와 CT를 이용하여 측정한 전기 부하의 전류 파형을 FFT 알고리즘을 적용한 후 신경회로망을 이용하여 단일부하패턴 분류 실험을 하였다. 본 연구를 통하여 부하의 특성을 파악함으로서 고장에 대해 보다 신속하고 정확하게 대처할 수 있을 것으로 예측된다.

Transfer length of 2400 MPa seven-wire 15.2 mm steel strands in high-strength pretensioned prestressed concrete beam

  • Yang, Jun-Mo;Yim, Hong-Jae;Kim, Jin-Kook
    • Smart Structures and Systems
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    • 제17권4호
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    • pp.577-591
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    • 2016
  • In this study, the transfer length of 2400 MPa, seven-wire high-strength steel strands with a 15.2 mm diameter in pretensioned prestressed concrete (PSC) beams utilizing high strength concrete over 58 MPa at prestress release was evaluated experimentally. 32 specimens, which have the variables of concrete compressive strength, concrete cover depth, and the number of PS strands, were fabricated and corresponding transfer lengths were measured. The strands were released gradually by slowly reducing the pressure in the hydraulic stressing rams. The measured results of transfer length showed that the transfer length decreased as the concrete compressive strength and concrete cover depth increased. The number of strands had a very small effect, and the effect varied with both the concrete cover depth and concrete strength. The results were compared to current design codes and transfer lengths predicted by other researchers. The comparison results showed that the current transfer length prediction models in design codes may be conservatively used for 2400 MPa high-strength strands in high-strength concrete beams exceeding 58 MPa at prestress release.

Evaluation of freezing and thawing damage of concrete using a nonlinear ultrasonic method

  • Yim, Hong Jae;Park, Sun-Jong;Kim, Jae Hong;Kwak, Hyo-Gyong
    • Smart Structures and Systems
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    • 제17권1호
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    • pp.45-58
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    • 2016
  • Freezing and thawing cycles induce deterioration and strength degradation of concrete structures. This study presumes that a large quantity of contact-type defects develop due to the freezing and thawing cycles of concrete and evaluates the degree of defects based on a nonlinearity parameter. The nonlinearity parameter was obtained by an impact-modulation technique, one of the nonlinear ultrasonic methods. It is then used as an indicator of the degree of contact-type defects. Five types of damaged samples were fabricated according to different freezing and thawing cycles, and the occurrence of opening or cracks on a micro-scale was visually verified via scanning electron microscopy. Dynamic modulus and wave velocity were also measured for a sensitivity comparison with the obtained nonlinearity parameter. The possibility of evaluating strength degradation was also investigated based on a simple correlation of the experimental results.

Vibration control for serviceability enhancement of offshore platforms against environmental loadings

  • Lin, Chih-Shiuan;Liu, Feifei;Zhang, Jigang;Wang, Jer-Fu;Lin, Chi-Chang
    • Smart Structures and Systems
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    • 제24권3호
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    • pp.403-414
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    • 2019
  • Offshore drilling has become a key process for obtaining oil. Offshore platforms have many applications, including oil exploration and production, navigation, ship loading and unloading, and bridge and causeway support. However, vibration problems caused by severe environmental loads, such as ice, wave, wind, and seismic loads, threaten the functionality of platform facilities and the comfort of workers. These concerns may result in piping failures, unsatisfactory equipment reliability, and safety concerns. Therefore, the vibration control of offshore platforms is essential for assuring structural safety, equipment functionality, and human comfort. In this study, an optimal multiple tuned mass damper (MTMD) system was proposed to mitigate the excessive vibration of a three-dimensional offshore platform under ice and earthquake loadings. The MTMD system was designed to control the first few dominant coupled modes. The optimal placement and system parameters of the MTMD are determined based on controlled modal properties. Numerical simulation results show that the proposed MTMD system can effectively reduce the displacement and acceleration responses of the offshore platform, thus improving safety and serviceability. Moreover, this study proposes an optimal design procedure for the MTMD system to determine the optimal location, moving direction, and system parameters of each unit of the tuned mass damper.

Flexural performances of deep-deck plate slabs: Experimental and numerical approaches

  • Inwook Heo;Sun-Jin Han;Khaliunaa Darkhanbat;Seung-Ho Choi;Sung Bae Kim;Kang Su Kim
    • Steel and Composite Structures
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    • 제52권3호
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    • pp.313-325
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    • 2024
  • This work presents experimental and numerical investigations on the flexural performances of composite deep-deck plate slabs. Seven deep-deck plate slab specimens with topping concrete were fabricated; the height of the topping slab as well as presence and type of shear connector were set as the main variables to perform bending experiments. The flexural behaviors of the specimens and composite behaviors of the deck plate and concrete were analyzed in detail. The contributions of the deck plate to the flexural stiffness and strength of the slab were identified through finite element (FE) analysis. FE analysis was carried out using the validated FE model by considering the varying bond strengths of the deck plates and concrete, thickness of the deck plate, and types and spacings of the shear connectors. Based on the results, the degree of composite of the deep-deck plate was examined, and a flexural strength equation for the composite deck plate slabs was proposed.

머신러닝 기법을 활용한 낙동강 하구 염분농도 예측 (Nakdong River Estuary Salinity Prediction Using Machine Learning Methods)

  • 이호준;조민규;천세진;한정규
    • 스마트미디어저널
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    • 제11권2호
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    • pp.31-38
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    • 2022
  • 하천의 염분 변화를 신속히 예측하는 것은 염분 침투로 인한 농업, 생태계의 피해를 예측하고 재해 방지 대책을 수립하기 위해서 중요한 작업이다. 머신러닝 기법은 물리 기반 수리 모델에 비해 계산량이 훨씬 적기 때문에, 비교적 짧은 시간에 염분농도를 예측 가능하여 물리 기반 수리 모델의 보완 기법으로 연구되고 있다. 해외에서는 머신러닝 기법 기반 염분 예측 연구들이 활발히 연구되고 있으나, 대한민국의 공공데이터에 머신러닝 기법을 적용한 연구는 충분치 않다. 낙동강 하구의 환경 정보에 관한 공공데이터와 함께, 본 연구는 여러 종류의 머신러닝 기법의 염분농도에 대한 예측 성능을 측정하였다. 실험 결과에서, 결정 트리 기반의 LightGBM 알고리즘은 평균 RMSE 0.37의 예측 정확도와 타 알고리즘 대비 2-20배 빠른 학습 속도를 보여주었다. 따라서 국내 하천의 염분농도 예측에도 머신러닝 기법을 적용할 수 있다고 판단된다.

AHP 분석을 통한 공동주택 안전 및 안심생활 수준 향상에 관한 연구 (A Study on the Improvement of the Safety and Safe Living Standards of Apartment Houses through AHP Analysis)

  • 지영일;신승하;최병정
    • 한국재난정보학회 논문집
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    • 제17권2호
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    • pp.289-305
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    • 2021
  • 연구목적: "AHP 분석을 통한 공동주택 입주민의 안전 및 안심생활 수준 향상"을 위하여 상위계층과 sub 상위계층, 하위대안 요소의 중요도 및 안심생활을 위한 요인을 확인하며, 종합우선도를 확인하고자 한다. 연구방법: 본 연구에서는 공동주택 유지보수 및 제도에 관한 선행연구와 전문가 자문을 토대로 안전관리 평가요소 및 대안을 계층 구조화하였다. 연구 모형은 전문가를 상대로 쌍대비교 구성의 설문에 활용하고, 대체안 순위 결정 등을 위해 AHP분석 기법을 사용 하였다. 연구결과: 설문조사 응답 결과는 일관성을 확보하였고, 연구의 최종 목표 달성을 위해 sub상위계층 그리고 대안을 상대적 가중치 비교 등을 분석한 결과 상위계층은 공동주택 전기설비 안전점검, sub 상위계층은 안전점검/정밀점검/진단평가, 대안은 급·배수시설이 최우선적으로 중요한 것으로 확인되었다. 결론: 공동주택관리 전문가의 관리자적 시각으로 볼 때 급·배수시설, 방범안전, 전기안전이 최우선적인 대안으로 나타났다. 이는 생활안전사고의 중요성을 확보하고 안심생활의 수준 향상이 가능한 것으로 의사 결정되어 사전 예방 및 관리 강화의 대안임을 보여 주었다.

사례분석을 통한 객체검출 기술의 건설현장 적용 방안에 관한 연구 (A Study on the Application of Object Detection Method in Construction Site through Real Case Analysis)

  • 이기석;강성원;신윤석
    • 한국재난정보학회 논문집
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    • 제18권2호
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    • pp.269-279
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    • 2022
  • 연구목적: 본 연구의 목적은 건설현장의 재해 예방을 위해 딥러닝기반의 개인보호구 검출 모델을 개발하고, 실제 건설현장에 적용하여 분석하는 것이다. 연구방법: 본 연구의 수행 방법은 실제 환경의 데이터를 구축하고, 개발된 개인보호구 검출 모델을 적용하였다. 개인보호구 검출 모델은 크게 근로자 검출 및 개인보호구 착용 분류 모델로 구성되어 있다. 근로자 검출 모델은 딥러닝 기반의 알고리즘을 실제 현장에서 획득한 데이터셋을 구축하여 학습 및 근로자를 검출하였고, 개인보호구 착용 분류 모델은 앞단에서 추출된 근로자 검출영역에서 학습된 개인보호구 검출 알고리즘을 적용하였다. 구축된 모델의 검증을 위해 건설현장 3곳에서 획득된 데이터를 통해 실험결과를 도출하였다. 연구결과: 데이터베이스 12,000장을 구축하여 정상검출 9,460장(78.8%), 오검출 1,468(12.2%), 미검출 1,072장(8.9%)으로 나타났으며 주요 원인은 영상에서의 객체 크기, 객체간 중첩(Occulusion), 객체 잘림, 그림자에 의한 오검출로 분류되었다. 결론: 개인보호구 검출모델은 현장 상황마다 다른 검출률을 확인할 수 있었고, 본 연구의 결과가 차후 현장적용을 위한 연구에 활용될 수 있을 것으로 여겨진다.

해안매립 신도시의 재해 예방관리 네트워크 비젼 (Network vision of disaster prevention management for seashore reclaimed u-City)

  • 안상로
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2009년도 세계 도시지반공학 심포지엄
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    • pp.117-129
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    • 2009
  • This paper studied the safety management network system of infrastructure which constructed smart sensors, closed-circuit television(CCTV) and monitoring system. This safety management of infrastructure applied to bridge, cut slop and tunnel, embankment etc. The system applied to technologies of standardization guidelines, data acquirement technologies, data analysis and judgment technologies, system integration setup technology, and IT technologies. It was constructed safety management network system of various infrastructure to improve efficient management and operation for many infrastructure. Integrated safety management network system of infrastructure consisted of the real-time structural health monitoring system of each infrastructure, integrated control center, measured data transmission using i of tet web-based, collecting data using sf ver, early alarm system which the dangerous event of infrastructure occurred. Integrated control center consisted of conference room, control room to manage and analysis the data, server room to present the measured data and to collect the raw data. Early alarm system proposed realization of warning and response within 5 minute or less through development of sensor-based progress report and propagation automation system using the media such as MMS, VMS, EMS, FMS, SMS and web services of report and propagation. Based on this, the most effective u-Infrastructure Safety Management System is expected to be stably established at a less cost, thus making people's life more comfortable. Information obtained from such systems could be useful for maintenance or structural safety evaluation of existing structures, rapid evaluation of conditions of damaged structures after an earthquake, estimation of residual life of structures, repair and retrofitting of structures, maintenance, management or rehabilitation of historical structures.

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