Smart Structures and Systems

테크노프레스 (Techno-Press)
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Operational modal analysis for Canton Tower

  • 투고 : 2012.02.17
  • 심사 : 2012.04.25
  • 발행 : 2012.10.25
⟨ 이전 논문 다음 논문 ⟩

초록

The 610 m high Canton Tower (formerly named Guangzhou New Television Tower) is currently considered as a benchmark problem for structural health monitoring (SHM) of high-rise slender structures. In the benchmark study task I, a set of 24-hour ambient vibration measurement data has been available for the output-only system identification study. In this paper, the vector autoregressive models (ARV) method is adopted in the operational modal analysis (OMA) for this TV tower. The identified natural frequencies, damping ratios and mode shapes are presented and compared with the available results from some other research groups which used different methods, e.g., the data-driven stochastic subspace identification (SSI-DATA) method, the enhanced frequency domain decomposition (EFDD) algorithm, and an improved modal identification method based on NExT-ERA technique. Furthermore, the environmental effects on the estimated modal parameters are also discussed.

키워드

참고문헌

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피인용 문헌

  1. Dynamic displacements-based model updating with motion capture system vol.24, pp.4, 2017, https://doi.org/10.1002/stc.1904
  2. Online Simultaneous Reconstruction of Wind Load and Structural Responses-Theory and Application to Canton Tower vol.30, pp.8, 2015, https://doi.org/10.1111/mice.12134
  3. Real-time structural health monitoring of a supertall building under construction based on visual modal identification strategy vol.85, 2018, https://doi.org/10.1016/j.autcon.2017.10.025
  4. New insights into coherence analysis with a view towards extracting structural natural frequencies under operational conditions vol.77, 2016, https://doi.org/10.1016/j.measurement.2015.08.038
  5. Operational modal analysis of Canton Tower by a fast frequency domain Bayesian method vol.17, pp.2, 2016, https://doi.org/10.12989/sss.2016.17.2.209
  6. Vision-based system identification technique for building structures using a motion capture system vol.356, 2015, https://doi.org/10.1016/j.jsv.2015.07.011
  7. Mono-Component Feature Extraction for Condition Assessment in Civil Structures Using Empirical Wavelet Transform vol.19, pp.19, 2012, https://doi.org/10.3390/s19194280
  8. Effect of soil-structure interaction on a masonry structure under train-induced vibrations vol.172, pp.12, 2012, https://doi.org/10.1680/jstbu.18.00131
  9. Modal analysis of structures based on distributed measurement of dynamic strains with optical fibers vol.159, pp.None, 2021, https://doi.org/10.1016/j.ymssp.2021.107835