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Corrosion Detection in PSC Bridge Tendons Using Kernel PCA Denoising of Measured MFL Signals
The construction of prestressed concrete bridges has witnessed a steep increase for the past 50 years worldwide. The constructed bridges exposed to various environmental conditions deteriorate all along their service life. One such degradation is corrosion, which can cause significant damage if it o...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7672632/ https://www.ncbi.nlm.nih.gov/pubmed/33105752 http://dx.doi.org/10.3390/s20215984 |
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author | Oh, Chang Kook Joh, Changbin Lee, Jung Woo Park, Kwang-Yeun |
author_facet | Oh, Chang Kook Joh, Changbin Lee, Jung Woo Park, Kwang-Yeun |
author_sort | Oh, Chang Kook |
collection | PubMed |
description | The construction of prestressed concrete bridges has witnessed a steep increase for the past 50 years worldwide. The constructed bridges exposed to various environmental conditions deteriorate all along their service life. One such degradation is corrosion, which can cause significant damage if it occurs on the main structural components, such as prestressing tendons. In this study, a novel non-destructive evaluation method to incorporate a movable yoke system with denoising algorithm based on kernel principal component analysis is developed and applied to identify the loss of cross-sectional area in corroded external prestressing tendons. The proposed method using denoised output voltage signals obtained from the measuring device appears to be a reliable and precise monitoring system to detect corrosion with less than 3% sectional loss. |
format | Online Article Text |
id | pubmed-7672632 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-76726322020-11-19 Corrosion Detection in PSC Bridge Tendons Using Kernel PCA Denoising of Measured MFL Signals Oh, Chang Kook Joh, Changbin Lee, Jung Woo Park, Kwang-Yeun Sensors (Basel) Article The construction of prestressed concrete bridges has witnessed a steep increase for the past 50 years worldwide. The constructed bridges exposed to various environmental conditions deteriorate all along their service life. One such degradation is corrosion, which can cause significant damage if it occurs on the main structural components, such as prestressing tendons. In this study, a novel non-destructive evaluation method to incorporate a movable yoke system with denoising algorithm based on kernel principal component analysis is developed and applied to identify the loss of cross-sectional area in corroded external prestressing tendons. The proposed method using denoised output voltage signals obtained from the measuring device appears to be a reliable and precise monitoring system to detect corrosion with less than 3% sectional loss. MDPI 2020-10-22 /pmc/articles/PMC7672632/ /pubmed/33105752 http://dx.doi.org/10.3390/s20215984 Text en © 2020 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 Oh, Chang Kook Joh, Changbin Lee, Jung Woo Park, Kwang-Yeun Corrosion Detection in PSC Bridge Tendons Using Kernel PCA Denoising of Measured MFL Signals |
title | Corrosion Detection in PSC Bridge Tendons Using Kernel PCA Denoising of Measured MFL Signals |
title_full | Corrosion Detection in PSC Bridge Tendons Using Kernel PCA Denoising of Measured MFL Signals |
title_fullStr | Corrosion Detection in PSC Bridge Tendons Using Kernel PCA Denoising of Measured MFL Signals |
title_full_unstemmed | Corrosion Detection in PSC Bridge Tendons Using Kernel PCA Denoising of Measured MFL Signals |
title_short | Corrosion Detection in PSC Bridge Tendons Using Kernel PCA Denoising of Measured MFL Signals |
title_sort | corrosion detection in psc bridge tendons using kernel pca denoising of measured mfl signals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7672632/ https://www.ncbi.nlm.nih.gov/pubmed/33105752 http://dx.doi.org/10.3390/s20215984 |
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