Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Oh, Chang Kook, Joh, Changbin, Lee, Jung Woo, Park, Kwang-Yeun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
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
_version_ 1783611176312111104
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
work_keys_str_mv AT ohchangkook corrosiondetectioninpscbridgetendonsusingkernelpcadenoisingofmeasuredmflsignals
AT johchangbin corrosiondetectioninpscbridgetendonsusingkernelpcadenoisingofmeasuredmflsignals
AT leejungwoo corrosiondetectioninpscbridgetendonsusingkernelpcadenoisingofmeasuredmflsignals
AT parkkwangyeun corrosiondetectioninpscbridgetendonsusingkernelpcadenoisingofmeasuredmflsignals