Automated data interpretation for modal identification of a truss bridge

J. Zhang, F. L. Moon, E. A. Aktan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Various kinds of uncertainty involved in bridge field test data leads to a number of extraneous modes which are difficult to be separated from real structural modes, thus making automatic data interpretation be a challenge in structural identification (St-Id) area. A practical St-Id procedure consisting of multi-level data pre-processing techniques and a vector backward auto-regressive (VBAR) method is proposed in this article for automatic data interpretation. In contrast to the difficulty to manually separate structure modes from extraneous modes in most traditional modal identification methods, the VBAR method provides a determinative way to automatically distinguish them. The proposed data pre-processing strategies play a key role to mitigate uncertainty and improve data quality. Without them, the subsequent data post-processing may meet problems. Ambient test data of a cantilever beam is studied to show how the proposed St-Id procedure automatically interprets test data. St-Id of a long-span truss bridge using field test data is performed to illustrate that the proposed method is effective for real bridge identification.

Original languageEnglish (US)
Title of host publicationStructural Health Monitoring 2011
Subtitle of host publicationCondition-Based Maintenance and Intelligent Structures - Proceedings of the 8th International Workshop on Structural Health Monitoring
Pages1045-1052
Number of pages8
StatePublished - 2011
Externally publishedYes
Event8th International Workshop on Structural Health Monitoring 2011: Condition-Based Maintenance and Intelligent Structures - Stanford, CA, United States
Duration: Sep 13 2011Sep 15 2011

Publication series

NameStructural Health Monitoring 2011: Condition-Based Maintenance and Intelligent Structures - Proceedings of the 8th International Workshop on Structural Health Monitoring
Volume1

Other

Other8th International Workshop on Structural Health Monitoring 2011: Condition-Based Maintenance and Intelligent Structures
CountryUnited States
CityStanford, CA
Period9/13/119/15/11

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering

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