Structural Monitoring and Maintenance

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A FRF-based algorithm for damage detection using experimentally collected data

  • Garcia-Palencia, Antonio (HNTB Corporation) ;
  • Santini-Bell, Erin (Department of Civil Engineering, University of New Hampshire) ;
  • Gul, Mustafa (Department of Civil and Enviromental Engineering, University of Alberta Canada) ;
  • Catbas, Necati (Department of Civil and Environmental and Construction Engineering, University of Central Florida)
  • Received : 2015.07.29
  • Accepted : 2015.11.27
  • Published : 2015.12.25
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Abstract

Automated damage detection through Structural Health Monitoring (SHM) techniques has become an active area of research in the bridge engineering community but widespread implementation on in-service infrastructure still presents some challenges. In the meantime, visual inspection remains as the most common method for condition assessment even though collected information is highly subjective and certain types of damage can be overlooked by the inspector. In this article, a Frequency Response Functions-based model updating algorithm is evaluated using experimentally collected data from the University of Central Florida (UCF)-Benchmark Structure. A protocol for measurement selection and a regularization technique are presented in this work in order to provide the most well-conditioned model updating scenario for the target structure. The proposed technique is composed of two main stages. First, the initial finite element model (FEM) is calibrated through model updating so that it captures the dynamic signature of the UCF Benchmark Structure in its healthy condition. Second, based upon collected data from the damaged condition, the updating process is repeated on the baseline (healthy) FEM. The difference between the updated parameters from subsequent stages revealed both location and extent of damage in a "blind" scenario, without any previous information about type and location of damage.

Keywords

Acknowledgement

Supported by : National Science Foundation

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