Modal parameter identification from measurements of vehicle-bridge interaction

Yi Liu*, John MacDonald, Dario Di Maio

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

2 Citations (Scopus)


The rise of output-only modal analysis has offered an economical and efficient way to identify modal parameters of civil engineering structures, namely natural frequencies, damping ratios and mode shapes. However, since the forcing is unknown, it is not possible to directly estimate modal masses, and estimates of damping ratios may be inaccurate. With the advancement of wireless sensor networks both vehicle and bridge responses can be simultaneously measured. This offers the possibility of estimating true Frequency Response Functions (FRFs), since the vehicle acceleration gives an estimate of the force input to the bridge. Hence in principle it is possible to estimate modal masses and more accurate damping ratios. However, the spatial and temporal variation of the moving load from a passing vehicle gives challenges to this idea and precludes the direct use of existing single-input-multiple-output (SIMO) system identification methods. Even if the system is treated as a multiple-input-multiple-output (MIMO) one, the inputs are highly correlated so existing methods for these systems are not applicable either. For this reason, a two-stage strategy is proposed to modify an existing method to solve this moving load problem.

Original languageEnglish
Title of host publicationDynamics of Civil Structures, Volume 2 - Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics 2018
EditorsShamim Pakzad
PublisherSpringer New York LLC
Number of pages3
ISBN (Print)9783319744209
Publication statusE-pub ahead of print - 12 Jun 2019
EventSEM Annual Conference and Exposition on Experimental and Applied Mechanics, 2018 - Greenville, United States
Duration: 4 Jun 20187 Jun 2018

Publication series

NameConference Proceedings of the Society for Experimental Mechanics Series
ISSN (Print)2191-5644
ISSN (Electronic)2191-5652


ConferenceSEM Annual Conference and Exposition on Experimental and Applied Mechanics, 2018
Country/TerritoryUnited States


  • Input-output
  • Modal mass
  • Mode superposition
  • Moving vehicle
  • System identification


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