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.
[1]
Arnold Neumaier,et al.
Algorithm 808: ARfit—a matlab package for the estimation of parameters and eigenmodes of multivariate autoregressive models
,
2001,
TOMS.
[2]
Weihua Chen,et al.
Monitoring Dynamic Characteristics for a Supertall Structure under Different Loading Events
,
2011
.
[3]
Yi-Qing Ni,et al.
Health Checks through Landmark Bridges to Sky-High Structures
,
2011
.
[4]
Yi-Qing Ni,et al.
Technology innovation in developing the structural health monitoring system for Guangzhou New TV Tower
,
2009
.
[5]
Yi-Qing Ni,et al.
Theoretical and experimental modal analysis of the Guangzhou New TV Tower
,
2011
.
[6]
Arnold Neumaier,et al.
Estimation of parameters and eigenmodes of multivariate autoregressive models
,
2001,
TOMS.