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Research Papers

Substructural Response Reconstruction in Wavelet Domain

[+] Author and Article Information
J. Li

Department of Civil and Structural Engineering, Hong Kong Polytechnic University, Hunghom, Kowloon, Hong Kong SAR07901542r@polyu.edu.hk

S. S. Law

Department of Civil and Structural Engineering, Hong Kong Polytechnic University, Hunghom, Kowloon, Hong Kong SARcesslaw@polyu.edu.hk

J. Appl. Mech 78(4), 041010 (Apr 13, 2011) (10 pages) doi:10.1115/1.4003738 History: Received June 10, 2010; Revised October 17, 2010; Posted March 02, 2011; Published April 13, 2011; Online April 13, 2011

An approach for structural response reconstruction in a substructure using the unit impulse response function in the wavelet domain is presented. The forces at the interface degrees-of-freedom are taken as input excitations on the substructure. The response reconstruction is conducted by transforming the measured responses into responses at other selected locations. The response reconstruction using the proposed wavelet domain method is then compared with that from an existing frequency domain method. Numerical studies on a seven-story plane frame structure are carried out to investigate the accuracy and effectiveness of the proposed method, and the effects of influencing parameters such as the number of sampled data, sampling rate, sensor numbers, and measurement noise are studied.

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Copyright © 2011 by American Society of Mechanical Engineers
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References

Figures

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Figure 5

Time domain analytical and reconstructed responses at node 34(θ)

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Figure 6

Measured acceleration response at sensor location node 15(x) with 10% noise

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Figure 1

Example of a substructure

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Figure 2

Finite element model of the frame structure

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Figure 3

A schematic excitation force p(t)

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Figure 4

Relative errors of response reconstruction in the time domain

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Figure 7

Relative errors in the response reconstruction results under 10% noise

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Figure 8

Analytical and reconstructed time domain responses at node 34(θ) under 10% noise

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Figure 9

Relative errors in the response reconstruction results without noise

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Figure 10

Relative errors in the response reconstruction results with 10% noise

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