Smart Structures and Systems

  • 제24권3호
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  • Pages.319-332
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  • 2019
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  • 1738-1584(pISSN)
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  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
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Online automatic structural health assessment of the Shanghai Tower

  • Zhang, Qilin (College of Civil Engineering, Tongji University) ;
  • Tang, Xiaoxiang (College of Civil Engineering, Tongji University) ;
  • Wu, Jie (College of Civil Engineering, Tongji University) ;
  • Yang, Bin (College of Civil Engineering, Tongji University)
  • 투고 : 2018.11.13
  • 심사 : 2019.07.11
  • 발행 : 2019.09.25
⟨ 이전 논문 다음 논문 ⟩

초록

Structural health monitoring (SHM) is of great importance to super high-rise buildings. The Shanghai Tower is currently the tallest building in China, and a complete SHM system was simultaneously constructed at the beginning of the construction of the tower. Due to the variety of sensor types and the large number of measurement points in the SHM system, an online automatic structural health assessment method with few computations and no manual intervention is needed. This paper introduces a structural health assessment method for the Shanghai Tower that uses the coefficients of an autoregressive (AR) time series model as structural state indicators. An analysis of collected data indicates that the coefficients of the AR model are affected by environmental factors, and the principal component analysis method is used to remove the influence of environmental factors. Finally, the control chart method is used to track the changes in structural state indicators, and a plan for online automatic structure health state evaluation is proposed. This method is applied to long-term acceleration and inclination data from the Shanghai Tower and successfully identifies the changes in the structural state. Overall, the structural state indicators of the Shanghai Tower are stable, and the structure is in a healthy state.

키워드

과제정보

연구 과제 주관 기관 : National Natural Science Fund of China (NSFC), Natural Science Foundation of Shanghai

참고문헌

  1. Abdelrazaq, A., Bentz, A., Kijewski-Correa, T., Guo, Y., Kwon, D.K., Kareem, A. and Bobby, S. (2013), "SmartSync: An integrated real-time structural health monitoring and structural identification system for tall buildings", J. Struct. Eng., 139(10), 1675-1687. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000560.
  2. Akaike, H. (1973), "Maximum likelihood identification of Gaussian autoregressive moving average models", Biometrika, 60(2), 255-265. https://doi.org/10.1093/biomet/60.2.255.
  3. Cornwell, P., Farrar, C.R., Doebling, S.W. and Sohn, H. (1999), "Environmental variability of modal properties", Exp. Techniques, 23(6), 45-48. https://doi.org/10.1111/j.1747-1567.1999.tb01320.x.
  4. de Lautour, O.R. and Omenzetter, P. (2010), "Damage classification and estimation in experimental structures using time series analysis and pattern recognition", Mech. Syst. Signal Pr., 24(5), 1556-1569. https://doi.org/10.1016/j.ymssp.2009.12.008.
  5. Ding, J.M., Chao, S., Zhao, X., and Wu, H.L. (2010), "Critical issues of structural analysis for the Shanghai Center project", J. Build. Struct., 31(6), 122-131. (In Chinese)
  6. Jolliffe, I. (2011), Principal component analysis, Springer, Berlin, Heidelberg, Germany.
  7. Liu, T., Yang, B. and Zhang, Q. (2016), "Health monitoring system developed for Tianjin 117 high-rise building", J. Aerosp. Eng., 30(2), B4016004. https://doi.org/10.1061/(ASCE)AS.1943-5525.0000602.
  8. Lu, Y. and Gao, F. (2005), "A novel time-domain auto-regressive model for structural damage diagnosis", J. Sound Vib., 283(3-5), 1031-1049. https://doi.org/10.1016/j.jsv.2004.06.030.
  9. Magalhaes, F., Cunha, A . and Caetano, E. (2009), "Online automatic identification of the modal parameters of a long span arch bridge", Mech. Syst. Signal Pr., 23(2), 316-329. https://doi.org/10.1016/j.ymssp.2008.05.003.
  10. Nair, K.K., Kiremidjian, A.S. and Law, K.H. (2006), "Time seriesbased damage detection and localization algorithm with application to the ASCE benchmark structure", J. Sound Vib., 291(1-2), 349-368. https://doi.org/10.1016/j.jsv.2005.06.016.
  11. Ni Y.Q., Xia Y., Liao W.Y. and Ko J.M. (2009), "Technology innovation in developing the structural health monitoring system for Guangzhou New TV Tower", Struct. Control Health Monit., 16(1), 73-98. https://doi.org/10.1002/stc.303.
  12. Peeters, B. and De Roeck, G. (2001), "One-year monitoring of the Z24-Bridge: environmental effects versus damage events", Earthq. Eng. Struct. D., 30(2), 149-171. https://doi.org/10.1002/1096-9845(200102)30:2<149::AIDEQE1>3.0.CO;2-Z
  13. Posenato, D., Lanata, F., Inaudi, D. and Smith, I.F.C. (2008), "Model-free data interpretation for continuous monitoring of complex structures", Adv. Eng. Inform., 22(1), 135-144. https://doi.org/10.1016/j.aei.2007.02.002.
  14. Reynders, E., Houbrechts, J. and De Roeck, G. (2012), "Fully automated (operational) modal analysis", Mech. Syst. Signal Pr., 29, 228-250. https://doi.org/10.1016/j.ymssp.2012.01.007.
  15. Shi, W., Shan, J. and Lu, X. (2012), "Modal identification of Shanghai World Financial Center both from free and ambient vibration response", Eng. Struct., 36 14-26. https://doi.org/10.1016/j.engstruct.2011.11.025.
  16. Sohn, H. and Farrar, C.R. (2001), "Damage diagnosis using time series analysis of vibration signals", Smart Mater. Struct., 10(3), 446-451. https://doi.org/10.1088/0964-1726/10/3/304
  17. Su, J., Xia, Y., Chen, L., Zhao, X., Zhang, Q., Xu, Y., Ding, J., Xiong, H., Ma, R. and Lv, X. (2013), "Long-term structural performance monitoring system for the Shanghai Tower", J. Civil Struct. Health Monit., 3(1), 49-61. https://doi.org/10.1007/s13349-012-0034-z
  18. Ubertini, F., Comanducci, G. and Cavalagli, N. (2016), "Vibration-based structural health monitoring of a historic belltower using output-only measurements and multivariate statistical analysis", Struct. Health Monit., 15(4), 438-457. https://doi.org/10.1177/1475921716643948.
  19. Ubertini, F., Gentile, C. and Materazzi, A.L. (2013), "Automated modal identification in operational conditions and its application to bridges", Eng. Struct., 46, 264-278. https://doi.org/10.1016/j.engstruct.2012.07.031.
  20. Yan, A.M., Kerschen, G., De Boe, P. and Golinval, J.C. (2005a), "Structural damage diagnosis under varying environmental conditions-Part I: A linear analysis", Mech. Syst. Signal Pr., 19(4), 847-864. https://doi.org/10.1016/j.ymssp.2004.12.002.
  21. Yan, A.M., Kerschen, G., De Boe, P. and Golinval, J.C. (2005b), "Structural damage diagnosis under varying environmental conditions-part II: local PCA for non-linear cases", Mech. Syst. Signal Pr., 19(4), 865-880. https://doi.org/10.1016/j.ymssp.2004.12.003.
  22. Yi, T., Li, H. and Zhang, X. (2015), "Health monitoring sensor placement optimization for Canton Tower using virus monkey algorithm", Smart Struct. Syst., 15(5), 1373-1392. http://dx.doi.org/10.12989/sss.2015.15.5.1373.
  23. Zhang, Q., Yang, B., Liu, T., Li, H. and Lv, J. (2015), "Structural health monitoring of Shanghai tower considering timedependent effects", Int. J. High-Rise Build., 4(1), 39-44. https://doi.org/10.21022/IJHRB.2015.4.1.039

피인용 문헌

  1. Monitoring dynamic characteristics of 600 m+ Shanghai Tower during two consecutive typhoons vol.28, pp.2, 2019, https://doi.org/10.1002/stc.2666