Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Zou, Yingquan, Chen, Yunpeng, Liu, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
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
_version_ 1783441370111803392
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
work_keys_str_mv AT zouyingquan refactoringandoptimizationofbridgedynamicdisplacementbasedonensembleempiricalmodedecomposition
AT chenyunpeng refactoringandoptimizationofbridgedynamicdisplacementbasedonensembleempiricalmodedecomposition
AT liupeng refactoringandoptimizationofbridgedynamicdisplacementbasedonensembleempiricalmodedecomposition