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Long-Term Structural Health Monitoring System for a High-Speed Railway Bridge Structure
Nanjing Dashengguan Bridge, which serves as the shared corridor crossing Yangtze River for both Beijing-Shanghai high-speed railway and Shanghai-Wuhan-Chengdu railway, is the first 6-track high-speed railway bridge with the longest span throughout the world. In order to ensure safety and detect the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4584230/ https://www.ncbi.nlm.nih.gov/pubmed/26451387 http://dx.doi.org/10.1155/2015/250562 |
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author | Ding, You-Liang Wang, Gao-Xin Sun, Peng Wu, Lai-Yi Yue, Qing |
author_facet | Ding, You-Liang Wang, Gao-Xin Sun, Peng Wu, Lai-Yi Yue, Qing |
author_sort | Ding, You-Liang |
collection | PubMed |
description | Nanjing Dashengguan Bridge, which serves as the shared corridor crossing Yangtze River for both Beijing-Shanghai high-speed railway and Shanghai-Wuhan-Chengdu railway, is the first 6-track high-speed railway bridge with the longest span throughout the world. In order to ensure safety and detect the performance deterioration during the long-time service of the bridge, a Structural Health Monitoring (SHM) system has been implemented on this bridge by the application of modern techniques in sensing, testing, computing, and network communication. The SHM system includes various sensors as well as corresponding data acquisition and transmission equipment for automatic data collection. Furthermore, an evaluation system of structural safety has been developed for the real-time condition assessment of this bridge. The mathematical correlation models describing the overall structural behavior of the bridge can be obtained with the support of the health monitoring system, which includes cross-correlation models for accelerations, correlation models between temperature and static strains of steel truss arch, and correlation models between temperature and longitudinal displacements of piers. Some evaluation results using the mean value control chart based on mathematical correlation models are presented in this paper to show the effectiveness of this SHM system in detecting the bridge's abnormal behaviors under the varying environmental conditions such as high-speed trains and environmental temperature. |
format | Online Article Text |
id | pubmed-4584230 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-45842302015-10-08 Long-Term Structural Health Monitoring System for a High-Speed Railway Bridge Structure Ding, You-Liang Wang, Gao-Xin Sun, Peng Wu, Lai-Yi Yue, Qing ScientificWorldJournal Research Article Nanjing Dashengguan Bridge, which serves as the shared corridor crossing Yangtze River for both Beijing-Shanghai high-speed railway and Shanghai-Wuhan-Chengdu railway, is the first 6-track high-speed railway bridge with the longest span throughout the world. In order to ensure safety and detect the performance deterioration during the long-time service of the bridge, a Structural Health Monitoring (SHM) system has been implemented on this bridge by the application of modern techniques in sensing, testing, computing, and network communication. The SHM system includes various sensors as well as corresponding data acquisition and transmission equipment for automatic data collection. Furthermore, an evaluation system of structural safety has been developed for the real-time condition assessment of this bridge. The mathematical correlation models describing the overall structural behavior of the bridge can be obtained with the support of the health monitoring system, which includes cross-correlation models for accelerations, correlation models between temperature and static strains of steel truss arch, and correlation models between temperature and longitudinal displacements of piers. Some evaluation results using the mean value control chart based on mathematical correlation models are presented in this paper to show the effectiveness of this SHM system in detecting the bridge's abnormal behaviors under the varying environmental conditions such as high-speed trains and environmental temperature. Hindawi Publishing Corporation 2015 2015-09-14 /pmc/articles/PMC4584230/ /pubmed/26451387 http://dx.doi.org/10.1155/2015/250562 Text en Copyright © 2015 You-Liang Ding et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ding, You-Liang Wang, Gao-Xin Sun, Peng Wu, Lai-Yi Yue, Qing Long-Term Structural Health Monitoring System for a High-Speed Railway Bridge Structure |
title | Long-Term Structural Health Monitoring System for a High-Speed Railway Bridge Structure |
title_full | Long-Term Structural Health Monitoring System for a High-Speed Railway Bridge Structure |
title_fullStr | Long-Term Structural Health Monitoring System for a High-Speed Railway Bridge Structure |
title_full_unstemmed | Long-Term Structural Health Monitoring System for a High-Speed Railway Bridge Structure |
title_short | Long-Term Structural Health Monitoring System for a High-Speed Railway Bridge Structure |
title_sort | long-term structural health monitoring system for a high-speed railway bridge structure |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4584230/ https://www.ncbi.nlm.nih.gov/pubmed/26451387 http://dx.doi.org/10.1155/2015/250562 |
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