한국전산구조공학회논문집 (Journal of the Computational Structural Engineering Institute of Korea)

  • 제34권5호
  • /
  • Pages.301-308
  • /
  • 2021
  • /
  • 1229-3059(pISSN)
  • /
  • 2287-2302(eISSN)
한국전산구조공학회 (Computational Structural Engineering Institute of Korea)
권호 표지
DOI QR코드

DOI QR Code

상시 교량 모니터링을 위한 저전력 IoT 센서 및 클라우드 기반 데이터 융합 변위 측정 기법 개발

Development of Low-Power IoT Sensor and Cloud-Based Data Fusion Displacement Estimation Method for Ambient Bridge Monitoring

  • 박준영 (중앙대학교 건설환경플랜트공학과) ;
  • 신준식 (중앙대학교 건설환경플랜트공학과) ;
  • 원종빈 (중앙대학교 토목공학과) ;
  • 박종웅 (중앙대학교 건설환경플랜트공학과) ;
  • 박민용 (반석안전주식회사)
  • Park, Jun-Young (Department of Civil Environmental & Plant Engineering, Chung-Ang University) ;
  • Shin, Jun-Sik (Department of Civil Environmental & Plant Engineering, Chung-Ang University) ;
  • Won, Jong-Bin (Department of Civil Engineering, Chung-Ang University) ;
  • Park, Jong-Woong (Department of Civil Environmental & Plant Engineering, Chung-Ang University) ;
  • Park, Min-Yong (Diagnosis Division, Banseok Safety Corporation)
  • 투고 : 2021.06.30
  • 심사 : 2021.08.25
  • 발행 : 2021.10.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

사회기반 시설물의 노후화에 대응해 이상 징후를 파악하고 유지보수를 위한 최적의 의사결정을 내리기 위해선 디지털 기반 SOC 시설물 유지관리 시스템의 개발이 필수적인데, 디지털 SOC 시스템은 장기간 구조물 계측을 위한 IoT 센서 시스템과 축적 데이터 처리를 위한 클라우드 컴퓨팅 기술을 요구한다. 본 연구에서는 구조물의 다물리량을 장기간 측정할 수 있는 IoT센서와 클라우드 컴퓨팅을 위한 서버 시스템을 개발하였다. 개발 IoT센서는 총 3축 가속도 및 3채널의 변형률 측정이 가능하고 24비트의 높은 해상도로 정밀한 데이터 수집을 수행한다. 또한 저전력 LTE-CAT M1 통신을 통해 데이터를 실시간으로 서버에 전송하여 별도의 중계기가 필요 없는 장점이 있다. 개발된 클라우드 서버는 센서로부터 다물리량 데이터를 수신하고 가속도, 변형률 기반 변위 융합 알고리즘을 내장하여 센서에서의 연산 없이 고성능 연산을 수행한다. 제안 방법의 검증은 2개소의 실제 교량에서 변위계와의 계측 결과 비교, 장기간 운영 테스트를 통해 이뤄졌다.

It is important to develop a digital SOC (Social Overhead Capital) maintenance system for preemptive maintenance in response to the rapid aging of social infrastructures. Abnormal signals induced from structures can be detected quickly and optimal decisions can be made promptly using IoT sensors deployed on the structures. In this study, a digital SOC monitoring system incorporating a multimetric IoT sensor was developed for long-term monitoring, for use in cloud-computing server for automated and powerful data analysis, and for establishing databases to perform : (1) multimetric sensing, (2) long-term operation, and (3) LTE-based direct communication. The developed sensor had three axes of acceleration, and five axes of strain sensing channels for multimetric sensing, and had an event-driven power management system that activated the sensors only when vibration exceeded a predetermined limit, or the timer was triggered. The power management system could reduce power consumption, and an additional solar panel charging could enable long-term operation. Data from the sensors were transmitted to the server in real-time via low-power LTE-CAT M1 communication, which does not require an additional gateway device. Furthermore, the cloud server was developed to receive multi-variable data from the sensor, and perform a displacement fusion algorithm to obtain reference-free structural displacement for ambient structural assessment. The proposed digital SOC system was experimentally validated on a steel railroad and concrete girder bridge.

키워드

과제정보

본 연구는 국토교통부/국토교통과학기술진흥원이 시행하는 "국토교통기술촉진연구사업(과제번호 21CTAP-C164014-01)"과 "스마트건설기술개발 국가R&D사업(과제번호 20SMIP-A158708-01)" 의지원으로 수행되었음.

참고문헌

  1. Brownjohn, J.M.W., Moyo, P., Omenzetter, P., Lu, Y. (2003) Assessment of Highway Bridge Upgrading by Dynamic Testing and Finite-Element Model Updating, J. Bridge Eng., 8(3), pp.162~172. https://doi.org/10.1061/(ASCE)1084-0702(2003)8:3(162)
  2. Farrar, C.R., Jauregui, D.A. (1998) Comparative Study of Damage Identification Algorithms Applied to a Bridge: I. Experiment, Smart Mater. & Struct., 7(5), p.704. https://doi.org/10.1088/0964-1726/7/5/013
  3. Fasl, J., Helwig, T., Wood, S.L., Pasupathy, P., Neikirk, D.P., Raffaeli, F. (2012) Factors Affecting Wireless Network Communication in Monitoring Systems for Steel Bridges, J. Civil Struct. Health Monit., 2(2), pp.87~95. https://doi.org/10.1007/s13349-012-0019-y
  4. Ferrari, R., Froio, D., Rizzi, E., Gentile, C., Chatzi, E.N. (2019) Model Updating of a Historic Concrete Bridge by Sensitivity-and Global Optimization-based Latin Hypercube Sampling, Eng. Struct., 179, pp.139~160. https://doi.org/10.1016/j.engstruct.2018.08.004
  5. Hoang, T., Fu, Y., Mechitov, K., Sanchez, F.G., Kim, J.R., Zhang, D., Spencer, B.F. (2020) Autonomous End-to-End Wireless Monitoring System for Railroad Bridges, Adv. Bridge Eng., 1(1), pp.1~27. https://doi.org/10.1186/s43251-020-00001-y
  6. Kim, E., Park, J.W., Sim. S.H. (2013) Dynamic behavior of Composite Steel Girder Bridge Exceeding Train Speed 350km/h, J. Korea Acad.-Ind., 14(7), pp.3518~3527.
  7. Kim, J.-H., Park, W.-J., Park, J.-O., Park, S.-H. (2018) LoRa LPWAN Sensor Network for Real-Time Monitoring and It's Control Method, J. Comput. Struct. Eng. Inst. Korea, 31(6), pp.359~366. https://doi.org/10.7734/COSEIK.2018.31.6.359
  8. Kurata, M., Kim, J., Lynch, J.P., van der Linden, G.W., Sedarat, H., Thometz, E., Hipley, P., Sheng, L.-H. (2013) Internet-Enabled Wireless Structural Monitoring Systems: Development and Permanent Deployment at the New Carquinez Suspension Bridge, J. Struct. Eng., 139(10), pp.1688~1702. https://doi.org/10.1061/(asce)st.1943-541x.0000609
  9. Lee, H.S., Hong, Y.H., Park, H.W. (2010) Design of an FIR Filter for the Displacement Reconstruction using Measured Acceleration in Low-Frequency Dominant Structures, Int. J. Numer. Methods Eng., 82(4), pp.403~434. https://doi.org/10.1002/nme.2769
  10. Lee, K., Kim, J., Ha, M., Cho, K. (2020) Measurement Management System using LoRa, Sensor Node, and Cloud Platform, J. Korean Soc. Hazard Mitig., 20(6), pp.143~150.
  11. Park, J. W., Sim, S. H., Jung, H. J. (2013) Displacement Estimation using Multimetric Data Fusion, IEEE/ASME Trans. Mechatron., 18(6), pp.1675~1682. https://doi.org/10.1109/TMECH.2013.2275187
  12. Seoul Facilities Corporation (2021) Chungdam1 Bridge Smart Load Capacity Assessment Report.
  13. Song, J.K., Jin, H.S., Chung, Y.H., Lee, S.W., Nam, W.H., Jang, D.H. (2008) Web-Based Bridge Monitoring System with Wireless Sensor Network Environment, J. Korean Soc. Hazard Mitig., 8(5), pp.35~44.