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Seismic Damage Identification Method for Curved Beam Bridges Based on Wavelet Packet Norm Entropy
Curved beam bridges, whose line type is flexible and beautiful, are an indispensable bridge type in modern traffic engineering. Nevertheless, compared with linear bridges, curved beam bridges have more complex internal forces and deformation due to the curvature; therefore, this type of bridge is mo...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8749680/ https://www.ncbi.nlm.nih.gov/pubmed/35009782 http://dx.doi.org/10.3390/s22010239 |
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author | Deng, Tongfa Huang, Jinwen Cao, Maosen Li, Dayang Bayat, Mahmoud |
author_facet | Deng, Tongfa Huang, Jinwen Cao, Maosen Li, Dayang Bayat, Mahmoud |
author_sort | Deng, Tongfa |
collection | PubMed |
description | Curved beam bridges, whose line type is flexible and beautiful, are an indispensable bridge type in modern traffic engineering. Nevertheless, compared with linear bridges, curved beam bridges have more complex internal forces and deformation due to the curvature; therefore, this type of bridge is more likely to suffer damage in strong earthquakes. The occurrence of damage reduces the safety of bridges, and can even cause casualties and property loss. For this reason, it is of great significance to study the identification of seismic damage in curved beam bridges. However, there is currently little research on curved beam bridges. For this reason, this paper proposes a damage identification method based on wavelet packet norm entropy (WPNE) under seismic excitation. In this method, wavelet packet transform is adopted to highlight the damage singularity information, the [Formula: see text] norm entropy of wavelet coefficient is taken as a damage characteristic factor, and then the occurrence of damage is characterized by changes in the damage index. To verify the feasibility and effectiveness of this method, a finite element model of Curved Continuous Rigid-Frame Bridges (CCRFB) is established for the purposes of numerical simulation. The results show that the damage index based on WPNE can accurately identify the damage location and characterize the severity of damage; moreover, WPNE is more capable of performing damage location and providing early warning than the method based on wavelet packet energy. In addition, noise resistance analysis shows that WPNE is immune to noise interference to a certain extent. As long as a series of frequency bands with larger correlation coefficients are selected for WPNE calculation, independent noise reduction can be achieved. |
format | Online Article Text |
id | pubmed-8749680 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87496802022-01-12 Seismic Damage Identification Method for Curved Beam Bridges Based on Wavelet Packet Norm Entropy Deng, Tongfa Huang, Jinwen Cao, Maosen Li, Dayang Bayat, Mahmoud Sensors (Basel) Article Curved beam bridges, whose line type is flexible and beautiful, are an indispensable bridge type in modern traffic engineering. Nevertheless, compared with linear bridges, curved beam bridges have more complex internal forces and deformation due to the curvature; therefore, this type of bridge is more likely to suffer damage in strong earthquakes. The occurrence of damage reduces the safety of bridges, and can even cause casualties and property loss. For this reason, it is of great significance to study the identification of seismic damage in curved beam bridges. However, there is currently little research on curved beam bridges. For this reason, this paper proposes a damage identification method based on wavelet packet norm entropy (WPNE) under seismic excitation. In this method, wavelet packet transform is adopted to highlight the damage singularity information, the [Formula: see text] norm entropy of wavelet coefficient is taken as a damage characteristic factor, and then the occurrence of damage is characterized by changes in the damage index. To verify the feasibility and effectiveness of this method, a finite element model of Curved Continuous Rigid-Frame Bridges (CCRFB) is established for the purposes of numerical simulation. The results show that the damage index based on WPNE can accurately identify the damage location and characterize the severity of damage; moreover, WPNE is more capable of performing damage location and providing early warning than the method based on wavelet packet energy. In addition, noise resistance analysis shows that WPNE is immune to noise interference to a certain extent. As long as a series of frequency bands with larger correlation coefficients are selected for WPNE calculation, independent noise reduction can be achieved. MDPI 2021-12-29 /pmc/articles/PMC8749680/ /pubmed/35009782 http://dx.doi.org/10.3390/s22010239 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Deng, Tongfa Huang, Jinwen Cao, Maosen Li, Dayang Bayat, Mahmoud Seismic Damage Identification Method for Curved Beam Bridges Based on Wavelet Packet Norm Entropy |
title | Seismic Damage Identification Method for Curved Beam Bridges Based on Wavelet Packet Norm Entropy |
title_full | Seismic Damage Identification Method for Curved Beam Bridges Based on Wavelet Packet Norm Entropy |
title_fullStr | Seismic Damage Identification Method for Curved Beam Bridges Based on Wavelet Packet Norm Entropy |
title_full_unstemmed | Seismic Damage Identification Method for Curved Beam Bridges Based on Wavelet Packet Norm Entropy |
title_short | Seismic Damage Identification Method for Curved Beam Bridges Based on Wavelet Packet Norm Entropy |
title_sort | seismic damage identification method for curved beam bridges based on wavelet packet norm entropy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8749680/ https://www.ncbi.nlm.nih.gov/pubmed/35009782 http://dx.doi.org/10.3390/s22010239 |
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