DOI QR코드

DOI QR Code

A Strain based Load Identification for the Safety Monitoring of the Steel Structure

철골 구조물의 안전성 모니터링을 위한 변형률 기반 하중 식별

  • 오병관 (연세대학교 건축공학과) ;
  • 이지훈 (대림산업(주)) ;
  • 최세운 (대구카톨릭대학교 건축공학과) ;
  • 김유석 (연세대학교 건축구조헬스케어연구단) ;
  • 박효선 (연세대학교 건축공학과)
  • Received : 2014.01.03
  • Accepted : 2014.01.27
  • Published : 2014.03.30

Abstract

This study proposes a load identification for the safety monitoring of the steel structure based on measured strain data. Instead of parameterizing the stiffness of structure in the existing system identification researches, the loads on a structure and a matrix (the unit strain matrix) defined by the relationship between strain and load on structure are parameterized in this study. The error function is defined by the difference between measured strain and strain estimated by parameters. In order to minimize this error function, the genetic algorithm which is one of the optimization algorithm is applied and the parameters are found. The loads on the structure can be identified through the founded parameters and measured strain data. When the loads are changed, the unmeasured strains are estimated based on founded parameters and measured strains on changed state of structure. To verify the load identification algorithm in this paper, the static experimental test for 3 dimensional steel frame structure was implemented and the loads were exactly identified through the measured strain data. In case of loading changes, the unmeasured strains which are monitoring targets on the structure were estimated in acceptable error range (0.17~3.13%). It is expected that the identification method in this study is applied to the safety monitoring of steel structures more practically.

본 연구에서는 철골 골조 구조물의 안전성 모니터링을 위하여 계측한 변형률을 통해 구조물에 작용한 하중을 식별하는 알고리즘을 제안한다. 기존의 시스템 식별 연구에서 구조물의 강성 등을 변수화한 것과는 다르게, 본 연구에서는 구조물에 작용한 하중과 이로 인해 구조물에 발생하는 변형률 간의 관계를 행렬로 정의하고, 이 행렬 및 작용한 하중을 변수화 한다. 계측한 변형률과 변수를 통해 추정한 변형률 사이의 차이를 오차함수로 설정하고 이를 최소화시키기 위해 최적화 알고리즘 중 하나인 유전자 알고리즘을 적용한다. 구해진 변수와 계측 변형률을 통해 작용한 하중을 식별하고 구조물의 하중 변화 시 미계측 지점의 응답을 추정한다. 본 연구에서 제안하는 하중 식별 알고리즘을 검증하기 위해 3차원 철골 골조 구조물의 정적 가력 실험을 수행하였고, 계측한 변형률을 통해 가해진 하중을 낮은 오차 수준으로 식별할 수 있었다. 또한, 하중 조건 변화 시, 계측한 변형률을 통해 모니터링 대상이 되는 미계측 지점의 변형률을 0.17~3.13%의 오차 범위로 추정하였다. 본 연구가 제안하는 식별법이 철골 구조물의 보다 현실적인 안전성 모니터링에 효과적으로 적용될 것으로 기대된다.

Keywords

References

  1. AISC (2005), Steel Construction Manual, American Institute of Steel Construction (AISC), Chicago, IL.
  2. Cho, N. S., Kim, N. S. (2008), Prediction of the Static Deflection Profiles on Suspension Bridge by Using FBG Strain Sensors, KSCE Journal of Civil Engineering, 28(5A), 699-707 (in Korean).
  3. Choi, S. W., Lee, J., Oh, B. H., and Park, H. S. (2013), Measurement model for the maximum strain in beam structures using multiplexed fiber bragg grating sensors, International Journal of Distributed Sensor Networks, Article ID 894780, 9.
  4. Choi, S. W., Lee, J., Oh, B. K., Park, H. S. (2013), Analytical models for estimation of the maximum strain of beam structures based on optical fiber bragg grating sensors, Journal of Civil Engineering and Management, 29(9), 707-717.
  5. De Jong K. A. (1975), An analysis of the behavior of a class of genetic adaptive systems, Doctoral Dissertation, University of Michigan.
  6. Goldberg D. E. (1989), Genetic algorithms in search, optimization and machine learning, Addison-Westley.
  7. Hahn, H. G., Ahn, H. J. (2012), A Study on Development of Structural Health Monitoring System for Steel Beams Using Strain Gauges, Journal of the Korea Institute for Structural Maintenance and Inspection, 16(1), 99-109 (in Korean). https://doi.org/10.11112/jksmi.2012.16.1.099
  8. Hampshire, T. A., Adeli, H. (2000), Monitoring the behavior of steel structures using distributed optical fiber sensor, Journal of Constructional Steel Research, 53(3), 267-281. https://doi.org/10.1016/S0143-974X(99)00043-7
  9. Hong, K., Lee, J., Choi, S. W., Kim, Y., Park, H. S. (2013), A strain-based load identification model for beams in building structures, Sensors, 13(8), 9909-9920. https://doi.org/10.3390/s130809909
  10. Jung, D. S., and Kim, C. Y. (2011), Finite element model updating on small-scale bridge model using the hybrid genetic algorithm, Structure and Infrastructure Engineering, 9(6), 481-495.
  11. Lee, H. M., Park, H. S. (2013), Measurement of maximum strain of steel beam structures based on average strains from vibrating wire strain gages, Experimental Techniques, 37(2), 23-29. https://doi.org/10.1111/j.1747-1567.2011.00733.x
  12. Lee, J. H., Choi, S. W., Park, H. S. (2013), A Regression-based Estimation of Strain Distribution for Safety Monitoring of the Steel Girder Subjected to Uncertain Loads, Journal of the Korea Institute for Structural Maintenance and Inspection, 17(2), 10-20 (in Korean). https://doi.org/10.11112/jksmi.2013.17.2.010
  13. Li, S., Wu, Z., Zhou, L. (2010), Health monitoring of flexural steel structures based on distributed fibre optic sensors, Structure and Infrastructure Engineering, 6(3), 303-315. https://doi.org/10.1080/15732470701492066
  14. Lioe, R., Wong, W. (2012), The Sands Hotel and Sands SkyPark, The Arup Journal, Issue 1, 17-20.
  15. Lozano-Galant, J. A. (2013), Application of observability techniques to structural system identification, Computer-Aided Civil and Infrastructure Engineering, 28(6), 434-450. https://doi.org/10.1111/mice.12004
  16. Lu, D., Cai, C. S. (2010), Bridge model updating using response surface method and genetic algorithm, Journal of bridge engineering, 15(5), 553-564. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000092
  17. Oh, B. K., Lee, J. H., Choi, S. W., Park, H. S., Kim, Y. (2014), A Estimation Method of Strain Distribution for Safety Monitoring of Multi-span Steel Beam Using FBG Sensor, Journal of the Korea Institute for Structural Maintenance and Inspection, 18(1), 138-149 (in Korean). https://doi.org/10.11112/jksmi.2014.18.1.138
  18. Park, H. S., Jung, H. S., Kwon, Y. H., Seo, J. H. (2006), Analytical models for assessment of the safety of steel beams based on average strains from long gage optic sensors, Sensors and Actuators A: Physical, 125, 109-113. https://doi.org/10.1016/j.sna.2005.04.038
  19. Park, H. S., Jung, S. M., Lee, H. M., Kwon, Y. H., Seo, J. H. (2007), Analytical models for assessment of the safety of multi-span steel beams based on average strains from long gage optic sensors, Sensors and Actuators A: Physical, 137(1), 6-12. https://doi.org/10.1016/j.sna.2007.01.015
  20. Park, H. S., Shin, Y., Choi, S. W., and Kim, Y. (2013), An Integrated Structural Health Monitoring System for the Local/Global Response of a Large-Scale Irregular Building under Construction, Sensors, 13, 9085-9103. https://doi.org/10.3390/s130709085
  21. Sanayei, M., Imbaro, G. R., McClain, J. A. S., Brown, L. C. (1997), Structural model updating using experimental static measurements, Journal of structural engineering, 123(6), 792-798. https://doi.org/10.1061/(ASCE)0733-9445(1997)123:6(792)
  22. Sanayei, M., Phelps, J. E., Sipple, J. D., Bell, E. S., Brenner, B. R. (2012), Instrumentation, nondestructive testing and finite-element model updating for bridge evaluation using strain measurements, Journal of bridge engineering, 17(1), 130-138. https://doi.org/10.1061/(ASCE)BE.1943-5592.0000228
  23. Sanayei, M., Rohela, P. (2014), Automated finite element model updating of full-scale structures with PARameter identification system(PARIS), Advances in Engineering Software, 67, 99-110. https://doi.org/10.1016/j.advengsoft.2013.09.002
  24. Tam, H., Au, H. Y., Chung, K. M., Liao, W. Y., Chung, W. H., Liu, S. Y., Lai, S. Y., Lai, C. C., Ni, Y. Q., Csipkes, A. (2011), Distribution Optical Sensor System on the 610-m Guangzhou New TV Tower, Optical Fiber Communication Conference, Los Angeles.