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Research Papers

Moving Load and Prestress Identification Using Wavelet-Based Method

[+] Author and Article Information
S. S. Law, S. Q. Wu

Civil and Structural Engineering Department, Hong Kong Polytechnic University, Hong Kong, People’s Republic of China

Z. Y. Shi

Research Institute of Structure and Strength, College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, People’s Republic of China

J. Appl. Mech 75(2), 021014 (Feb 26, 2008) (7 pages) doi:10.1115/1.2793134 History: Received October 04, 2006; Revised August 18, 2007; Published February 26, 2008

A novel moving force and prestress identification method based on finite element and wavelet-based method for bridge-vehicle system is developed. A two-axle vehicle model and simple-supported beam with prestressing force are studied. Finite element method is flexible in modeling structures with complex boundaries while the wavelet-analysis method has the characteristic of multiresolution and the ability to detect abrupt changes. Both methods are used in this work to identify the moving loads and prestressing force from the “measured” bridge responses, which may be strain or acceleration. Numerical simulations demonstrate the efficiency of the method under the effects of measurement noise, road roughness, sampling rate, and the arrangement of sensors with good accuracy. Results indicate that the proposed method has the advantages of both high computational performance and fine identification resolution.

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Copyright © 2008 by American Society of Mechanical Engineers
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Figures

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Figure 1

The vehicle-bridge system

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Figure 2

Identified moving forces with 5% noise and different resolutions (—true, ---- J=8, -.-.-.-J=10, ……J=11)

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Figure 3

Identified prestress force with 5% noise and different resolutions (—true)

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Figure 4

Identified moving forces on the prestressed bridge from different sensor arrangements with 5% noise and J=10 (—true, ---- Ns=4, -.-.-.- Ns=6, …. Ns=7)

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Figure 5

Identified prestress force from different sensor arrangements and 5% noise with J=10 (—true)

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