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Refactoring and Optimization of Bridge Dynamic Displacement Based on Ensemble Empirical Mode Decomposition
Considering the lack of precision in transforming measured micro-electro-mechanical system (MEMS) accelerometer output signals into elevation signals, this paper proposes a bridge dynamic displacement reconstruction method based on the combination of ensemble empirical mode decomposition (EEMD) and...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679592/ https://www.ncbi.nlm.nih.gov/pubmed/31311190 http://dx.doi.org/10.3390/s19143125 |
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author | Zou, Yingquan Chen, Yunpeng Liu, Peng |
author_facet | Zou, Yingquan Chen, Yunpeng Liu, Peng |
author_sort | Zou, Yingquan |
collection | PubMed |
description | Considering the lack of precision in transforming measured micro-electro-mechanical system (MEMS) accelerometer output signals into elevation signals, this paper proposes a bridge dynamic displacement reconstruction method based on the combination of ensemble empirical mode decomposition (EEMD) and time domain integration, according to the vibration signal traits of a bridge. Through simulating bridge analog signals and verifying a vibration test bench, four bridge dynamic displacement monitoring methods were analyzed and compared. The proposed method can effectively eliminate the influence of low-frequency integral drift and high-frequency ambient noise on the integration process. Furthermore, this algorithm has better adaptability and robustness. The effectiveness of the method was verified by field experiments on highway elevated bridges. |
format | Online Article Text |
id | pubmed-6679592 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-66795922019-08-19 Refactoring and Optimization of Bridge Dynamic Displacement Based on Ensemble Empirical Mode Decomposition Zou, Yingquan Chen, Yunpeng Liu, Peng Sensors (Basel) Article Considering the lack of precision in transforming measured micro-electro-mechanical system (MEMS) accelerometer output signals into elevation signals, this paper proposes a bridge dynamic displacement reconstruction method based on the combination of ensemble empirical mode decomposition (EEMD) and time domain integration, according to the vibration signal traits of a bridge. Through simulating bridge analog signals and verifying a vibration test bench, four bridge dynamic displacement monitoring methods were analyzed and compared. The proposed method can effectively eliminate the influence of low-frequency integral drift and high-frequency ambient noise on the integration process. Furthermore, this algorithm has better adaptability and robustness. The effectiveness of the method was verified by field experiments on highway elevated bridges. MDPI 2019-07-15 /pmc/articles/PMC6679592/ /pubmed/31311190 http://dx.doi.org/10.3390/s19143125 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zou, Yingquan Chen, Yunpeng Liu, Peng Refactoring and Optimization of Bridge Dynamic Displacement Based on Ensemble Empirical Mode Decomposition |
title | Refactoring and Optimization of Bridge Dynamic Displacement Based on Ensemble Empirical Mode Decomposition |
title_full | Refactoring and Optimization of Bridge Dynamic Displacement Based on Ensemble Empirical Mode Decomposition |
title_fullStr | Refactoring and Optimization of Bridge Dynamic Displacement Based on Ensemble Empirical Mode Decomposition |
title_full_unstemmed | Refactoring and Optimization of Bridge Dynamic Displacement Based on Ensemble Empirical Mode Decomposition |
title_short | Refactoring and Optimization of Bridge Dynamic Displacement Based on Ensemble Empirical Mode Decomposition |
title_sort | refactoring and optimization of bridge dynamic displacement based on ensemble empirical mode decomposition |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679592/ https://www.ncbi.nlm.nih.gov/pubmed/31311190 http://dx.doi.org/10.3390/s19143125 |
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