• Title/Summary/Keyword: 건전성모니터링

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Construction of wireless sensor network for structural health monitoring of large-scale buildings (대형 건물의 구조 건전도 모니터링을 위한 무선 센서 네트워크 구성)

  • Lee, Hong-Min;Kim, Jong-Moon;Hong, Jung-Bum;Park, Hyo-Seon
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2009.04a
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    • pp.221-224
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    • 2009
  • 최근 사회기반시설을 대상으로 900 MHz - 2.45 GHz 대역의 무선 센서 네트워크 시스템을 이용한 구조반응 모니터링 연구가 수행되고 있다. 건물의 경우 수직, 수평으로 구조 부재, 칸막이 벽, 외장재 등에 의해서 공간이 차단되어 있고, 전파 간섭의 영향이 상대적으로 크기 때문에 900 MHz - 2.4 GHz 대역의 무선 네트워크 시스템은 그 한계가 있다. 본 논문에서는 이러한 문제점을 고려하여 장애물에 대한 회절성이 뛰어나고 전파의 간섭이 상대적으로 작은 저주파 대역의 무선 라디오 주파수를 도입한다. 이로부터 특히 지진 또는 바람의 영향 등의 외부 하중에 의하여 대규모 인명 손실을 초래할 수 있는 중요도가 매우 높은 대형 건물을 대상으로 실제 적용이 가능한 무선 센서 네트워크를 구성해 보았다.

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Integrated Health Monitoring System for Infra-Structure (도시인프라 구조물 건전성 통합 모니터링 시스템)

  • Ju, Seung-Hwan;Seo, Hee-Suk;Lee, Seung-Hwan;Kim, Min-Soo
    • Journal of the Korea Society for Simulation
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    • v.19 no.2
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    • pp.147-155
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    • 2010
  • It often occur to nature disaster that like earthquake, typhoon, etc. around KOREA. A Haiti and Chile also metropolitan area of KOREA occur earthquake. in result, People consider nature disaster. Structures of present age are easily affected by nature disaster. So we are important that warn of dangerous situation as soon as possible. On this study, I introduce Integrated Health Monitoring System for Infra-structure. I develop Structure Health Monitoring System on web-site. Administrator always monitor structure on real-time using internet network. As Administrator using mobile device like PDA, Administrator always monitor structure. As using this system, Damage of nature disaster is minimized and is prevented post damage.

Baseline Model Updating and Damage Estimation Techniques for Tripod Substructure (트라이포드 하부구조물의 기저모델개선 및 결함추정 기법)

  • Lee, Jong-Won
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.6
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    • pp.218-226
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    • 2020
  • An experimental study was conducted on baseline model updating and damage estimation techniques for the health monitoring of offshore wind turbine tripod substructures. First, a procedure for substructure health monitoring was proposed. An initial baseline model for a scaled model of a tripod substructure was established. A baseline model was updated based on the natural frequencies and the mode shapes measured in the healthy state. A training pattern was then generated using the updated baseline model, and the damage was estimated by inputting the modal parameters measured in the damaged state into the trained neural network. The baseline model could be updated reasonably using the effective fixity model. The damage tests were performed, and the damage locations could be estimated reasonably. In addition, the estimated damage severity also increased as the actual damage severity increased. On the other hand, when the damage severity was relatively small, the corresponding damage location was detected, but it was more difficult to identify than the other cases. Further studies on small damage estimation and stiffness reduction quantification will be needed before the presented method can be used effectively for the health monitoring of tripod substructures.