Wavelet-Based Nonstationary Wind Speed Model in Dongting Lake Cable-Stayed Bridge
Author(s): |
Xuhui He
Jun Fang Andrew Scanlon Zhengqing Chen |
---|---|
Medium: | journal article |
Language(s): | English |
Published in: | Engineering, 2010, n. 11, v. 2 |
Page(s): | 895-903 |
DOI: | 10.4236/eng.2010.211113 |
Abstract: | The wind-rain induced vibration phenomena in the Dongting Lake Bridge (DLB) can be observed every year, and the field measurements of wind speed data of the bridge are usually nonstationary. Nonstationary wind speed can be decomposed into a deterministic time-varying mean wind speed and a zero-mean stationary fluctuating wind speed component. By using wavelet transform (WT), the time-varying mean wind speed is extracted and a nonstationary wind speed model is proposed in this paper. The wind characteristics of turbulence intensity, integral scale and probability distribution of the bridge are calculated from the typical wind samples recorded by the two anemometers installed on the DLB using the proposed nonstationary wind speed model based on WT. The calculated results are compared with those calculated by the empirical mode decomposition (EMD) and traditional approaches. The compared results indicate that the wavelet-based nonstationary wind speed model is more reasonable and appropriate than the EMD-based nonstationary and traditional stationary models for characterizing wind speed in analysis of wind-rain-induced vibration of cables. |
Keywords: |
cable-stayed bridge rain-wind-induced vibration
|
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
Structures and Projects
Structure Types
Download full text file (PDF)
0.43 MB
Advertisement
Advertisement
0.43 MB
- About this
data sheet - Reference-ID
10423428 - Published on:
08/06/2020 - Last updated on:
02/06/2021