Signature extraction from the dynamic responses of a bridge subjected to a moving vehicle using complete ensemble empirical mode decomposition
Technology that measures bridge responses when a vehicle is crossing over it for structural health monitoring has been under development for approximately a decade. Most of the proposed methods are based on identification of the dynamic characteristics of a bridge such as the natural frequency, the...
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Series: | Journal of Low Frequency Noise, Vibration and Active Control |
Online Access: | https://doi.org/10.1177/1461348419872878 |
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doaj-175ef4c87dd04817bae19ecf1c59fa252021-03-22T22:35:40ZengSAGE PublishingJournal of Low Frequency Noise, Vibration and Active Control1461-34842048-40462021-03-014010.1177/1461348419872878Signature extraction from the dynamic responses of a bridge subjected to a moving vehicle using complete ensemble empirical mode decompositionFeng XiaoGang S ChenWael ZatarJ Leroy HulseyTechnology that measures bridge responses when a vehicle is crossing over it for structural health monitoring has been under development for approximately a decade. Most of the proposed methods are based on identification of the dynamic characteristics of a bridge such as the natural frequency, the mode shapes, and the damping. Specifically, many time–frequency domain approaches have been used to extract complex spectrum signatures from the complicated vibrations of a bridge due to the interactions of a vehicle with the bridge, which usually involves nonlinear, nonstationary, stochastic, and impact vibrations. In this paper, a method known as complete ensemble empirical mode decomposition with adaptive noise is applied for the first time to analyze the acceleration response of a bridge to a moving vehicle, and the purpose is to extract the spectrum signature of the vehicle–bridge response for structural health monitoring. The time–frequency Hilbert-Huang transform (HHT) spectrum of the decomposed mode from complete ensemble empirical mode decomposition with adaptive noise is presented. The results are well-correlated with finite element analysis. The advantages of the complete ensemble empirical mode decomposition with adaptive noise method are demonstrated in comparing the data from conventional methods, including power spectra, spectrograms, scalograms, and empirical mode decomposition.https://doi.org/10.1177/1461348419872878 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Feng Xiao Gang S Chen Wael Zatar J Leroy Hulsey |
spellingShingle |
Feng Xiao Gang S Chen Wael Zatar J Leroy Hulsey Signature extraction from the dynamic responses of a bridge subjected to a moving vehicle using complete ensemble empirical mode decomposition Journal of Low Frequency Noise, Vibration and Active Control |
author_facet |
Feng Xiao Gang S Chen Wael Zatar J Leroy Hulsey |
author_sort |
Feng Xiao |
title |
Signature extraction from the dynamic responses of a bridge subjected to a moving vehicle using complete ensemble empirical mode decomposition |
title_short |
Signature extraction from the dynamic responses of a bridge subjected to a moving vehicle using complete ensemble empirical mode decomposition |
title_full |
Signature extraction from the dynamic responses of a bridge subjected to a moving vehicle using complete ensemble empirical mode decomposition |
title_fullStr |
Signature extraction from the dynamic responses of a bridge subjected to a moving vehicle using complete ensemble empirical mode decomposition |
title_full_unstemmed |
Signature extraction from the dynamic responses of a bridge subjected to a moving vehicle using complete ensemble empirical mode decomposition |
title_sort |
signature extraction from the dynamic responses of a bridge subjected to a moving vehicle using complete ensemble empirical mode decomposition |
publisher |
SAGE Publishing |
series |
Journal of Low Frequency Noise, Vibration and Active Control |
issn |
1461-3484 2048-4046 |
publishDate |
2021-03-01 |
description |
Technology that measures bridge responses when a vehicle is crossing over it for structural health monitoring has been under development for approximately a decade. Most of the proposed methods are based on identification of the dynamic characteristics of a bridge such as the natural frequency, the mode shapes, and the damping. Specifically, many time–frequency domain approaches have been used to extract complex spectrum signatures from the complicated vibrations of a bridge due to the interactions of a vehicle with the bridge, which usually involves nonlinear, nonstationary, stochastic, and impact vibrations. In this paper, a method known as complete ensemble empirical mode decomposition with adaptive noise is applied for the first time to analyze the acceleration response of a bridge to a moving vehicle, and the purpose is to extract the spectrum signature of the vehicle–bridge response for structural health monitoring. The time–frequency Hilbert-Huang transform (HHT) spectrum of the decomposed mode from complete ensemble empirical mode decomposition with adaptive noise is presented. The results are well-correlated with finite element analysis. The advantages of the complete ensemble empirical mode decomposition with adaptive noise method are demonstrated in comparing the data from conventional methods, including power spectra, spectrograms, scalograms, and empirical mode decomposition. |
url |
https://doi.org/10.1177/1461348419872878 |
work_keys_str_mv |
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