Smart Structures and Systems

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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)
  • Received : 2018.11.13
  • Accepted : 2019.07.11
  • Published : 2019.09.25
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Abstract

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.

Keywords

Acknowledgement

Supported by : National Natural Science Fund of China (NSFC), Natural Science Foundation of Shanghai

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