Automated data interpretation for practical bridge identification

  • Zhang, J. (Key Laboratory of C&RC Structures of the Ministry of Education, Southeast University) ;
  • Moon, F.L. (Drexel University) ;
  • Sato, T. (International Institute for Urban Systems Engineering, Southeast University)
  • Received : 2012.04.02
  • Accepted : 2013.04.24
  • Published : 2013.05.10


Vibration-based structural identification has become an important tool for structural health monitoring and safety evaluation. However, various kinds of uncertainties (e.g., observation noise) involved in the field test data obstruct automation system identification for accurate and fast structural safety evaluation. A practical way including a data preprocessing procedure and a vector backward auto-regressive (VBAR) method has been investigated for practical bridge identification. The data preprocessing procedure serves to improve the data quality, which consists of multi-level uncertainty mitigation techniques. The VBAR method provides a determinative way to automatically distinguish structural modes from extraneous modes arising from uncertainty. Ambient test data of a cantilever beam is investigated to demonstrate how the proposed method automatically interprets vibration data for structural modal estimation. Especially, structural identification of a truss bridge using field test data is also performed to study the effectiveness of the proposed method for real bridge identification.



Supported by : National Science Foundation of China


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