System Identification of a Base-Isolated Bridge by Ambient and Forced Vibration Tests

Sciarapotamo Bridge, located in Reggio Calabria Province, Italy, has been recently retrofitted by replacing its deteriorated concrete bridge deck with a composite steel- concrete deck, and isolating the new deck with eight high damping rubber, and four multi-directional sliding bearings. Full-scale ambient and forced vibration dynamic commissioning tests were performed on the bridge just before the bridge has become operational. Three different output-only system identification methods with ambient vibration measurements were used for modal parameter identification, namely: (1) multiple reference natural excitation technique in conjunction with eigen-system realization algorithm, (2) enhanced frequency domain decomposition, and (3) data driven stochastic subspace identification methods. Modal parameter estimation results using different output-only identification methods were presented and compared within the paper. In addition, relatively higher level forced vibration test data was used for estimating frequency response functions, identifying isolated natural frequencies, and damping ratios of the retrofitted bridge in as-built condition. Estimated damping coefficients under different excitation levels are of great value, showing the total damping in the system at low level ambient and relatively higher level forced vibration tests. Experimentally obtained modal parameters of the bridge set the undamaged benchmark state of the bridge for future potential condition assessment studies.

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    • © ASTM International 2017. All rights reserved. This material may not be reproduced or copied, in whole or part, in any printed, mechanical, electronic, film, or other distribution and storage media, without the written consent of the publisher.
  • Authors:
    • Ozcelik, O
    • Amaddeo, C
  • Publication Date: 2017-11


  • English

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  • Accession Number: 01691293
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jan 25 2019 10:31AM