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Proceedings Paper

Physics-based traffic excitation models for highway bridges
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Paper Abstract

For long-term bridge health monitoring, structural dynamic properties are usually obtained by system identification based only on the system output (bridge vibration responses), because the system input (traffic excitation) is difficult to measure. To facilitate such identification the excitation is commonly assumed as spatially uncorrelated white noise. However, when physically modeling it as a stationary stream of moving forces traversing the bridge, whose arrivals at the bridge are in accordance with a Poisson process, the traffic excitation is found to be spatially correlated. In this paper a procedure for formulating the traffic excitation model based on its physics is proposed, which involves first converting the moving forces into equivalent nodal excitation time-histories by the dynamic nodal loading approach, and then applying the Campbell’s theorem for the filtered Poisson processes. By this procedure, a non-diagonal frequency-variant excitation spectrum density matrix (SDM) is obtained. This does not conform to the conventional white noise excitation model. One of the output-only identification techniques based on the conventional excitation model, the frequency domain decomposition technique is implemented to demonstrate that direct application of the technique to traffic-induced vibrations can lead to misleading results. The proposed procedure for formulating the traffic excitation SDM provides a way to describe primary knowledge of the traffic excitation in frequency domain even for complicated bridges, which will potentially enable improvement in output-only identification techniques with unknown but spatially correlated excitation.

Paper Details

Date Published: 29 July 2004
PDF: 12 pages
Proc. SPIE 5391, Smart Structures and Materials 2004: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, (29 July 2004); doi: 10.1117/12.540041
Show Author Affiliations
Yangbo Chen, Univ. of California/Irvine (United States)
Chin-An Tan, Wayne State Univ. (United States)
Maria Q Feng, Univ. of California/Irvine (United States)


Published in SPIE Proceedings Vol. 5391:
Smart Structures and Materials 2004: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems
Shih-Chi Liu, Editor(s)

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