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Recently, the concept of "drive-by" bridge monitoring system using indirect measurements from a passing vehicle to extract key parameters of a bridge has been rapidly developed. As one of the most key parameters of a bridge, the natural frequency has been successfully extracted theoretically and in practice using indirect measurements. The frequency of bridge is generally calculated applying Fast Fourier Transform (FFT) directly. However, it has been demonstrated that with the increase in vehicle velocity, the estimated frequency resolution of FFT will be very low causing a great extracted error. Moreover, because of the low frequency resolution, it is hard to detect the frequency drop caused by any damages or degradation of the bridge structural integrity. This paper will introduce a new technique of bridge frequency extraction based on Hilbert Transform (HT) that is not restricted to frequency resolution and can, therefore, improve identification accuracy. In this paper, deriving from the vehicle response, the closed-form solution associated with bridge frequency removing the effect of vehicle velocity is discussed in the analytical study. Then a numerical Vehicle-Bridge Interaction (VBI) model with a quarter car model is adopted to demonstrate the proposed approach. Finally, factors that affect the proposed approach are studied, including vehicle velocity, signal noise, and road roughness profile.
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Wavelet Based Damage Assessment and Localization for Bridge Structures
Bridges as a key component of road networks require periodic monitoring to detect structural degradation for early warning. In term of maintaining the bridge safety, it is essential to estimate the damage location and extent. This paper hypothetically investigates employing the wavelet transform to analysis the signal of a vehicle/bridge system to localize and estimate the damage severity. The paper investigated the feasibility of using direct measurements from the bridge system, in compare with using indirect measurements from a crossing inspection vehicle. The study utilizes an implicit Vehicle-Bridge Interaction (VBI) algorithm to simulate the passage of the instrumented vehicle over the bridge to generate the signal; then the signals are processed using Wavelet Transform. The study found that using the indirect vehicle measurements is more sensitive to bridge damage since the vehicle acts as a moving sensor over the bridge. Further, the paper shows promising results for damage detection using the bridge displacement responses, if the static component of the displacement is removed from the recorded displacement history.
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- Award ID(s):
- 1645863
- PAR ID:
- 10089840
- Date Published:
- Journal Name:
- Chengjun Tan, Ahmed Elhattab, Nasim Uddin
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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