Damage Localization of RC Beams via Wavelet Analysis of Noise Contaminated Modal Curvatures

In this paper, the location of single, double, and triple damage scenarios in reinforced concrete (RC) beams are assessed using the Wavelet transform coefficient. To achieve this goal, the numerical models of RC concrete beams were conducted based on the experimental specimens. The mode shapes and c...

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Autores principales:	Hashem Jahangir, Hamed Hasani, Mohammad Reza Esfahani
Formato:	article
Lenguaje:	EN
Publicado:	Pouyan Press 2021
Materias:	damage location wavelet transform noisy contaminated condition modal curvature rc beams Technology T
Acceso en línea:	https://doaj.org/article/ed04cb04639e403a91c615bd997fb357
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spelling	oai:doaj.org-article:ed04cb04639e403a91c615bd997fb3572021-11-11T11:41:53ZDamage Localization of RC Beams via Wavelet Analysis of Noise Contaminated Modal Curvatures2588-287210.22115/scce.2021.292279.1340https://doaj.org/article/ed04cb04639e403a91c615bd997fb3572021-07-01T00:00:00Zhttp://www.jsoftcivil.com/article_139408_792993b98990ba630eeac3152df731e4.pdfhttps://doaj.org/toc/2588-2872In this paper, the location of single, double, and triple damage scenarios in reinforced concrete (RC) beams are assessed using the Wavelet transform coefficient. To achieve this goal, the numerical models of RC concrete beams were conducted based on the experimental specimens. The mode shapes and corresponding modal curvatures of the RC beam models in damaged and undamaged status were considered as input signals in Wavelet transform. By considering the Wavelet coefficient as damage index, Daubechies, Biorthogonal, and Reverse Biorthogonal Wavelet families were compared to select the most proper one to identify damage locations. Moreover, various sampling distances and their influence on the damage index were studied. In order to simulate the practical situations, two kinds of noises were added to modal data and then denoised by Wavelet analysis to check the proposed damage index in noisy conditions. The results revealed that among the wavelet families, rbio2.4 and rbio2.2 outperform others in detecting damage locations using mode shapes and modal curvatures, respectively. As expected, the sensitivity of modal curvatures to different damage scenarios is more the mode shapes. By increasing sampling distances from 25 mm to 100 mm, the accuracy of the proposed damage index reduces. In order to eliminate boundary effects, it is necessary to use windowing techniques. Applying Wavelet denoising methods on noise-contaminated modal curvatures leads to proper damage localization in both types of noises.Hashem JahangirHamed HasaniMohammad Reza EsfahaniPouyan Pressarticledamage locationwavelet transformnoisy contaminated conditionmodal curvaturerc beamsTechnologyTENJournal of Soft Computing in Civil Engineering, Vol 5, Iss 3, Pp 101-133 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	damage location wavelet transform noisy contaminated condition modal curvature rc beams Technology T
spellingShingle	damage location wavelet transform noisy contaminated condition modal curvature rc beams Technology T Hashem Jahangir Hamed Hasani Mohammad Reza Esfahani Damage Localization of RC Beams via Wavelet Analysis of Noise Contaminated Modal Curvatures
description	In this paper, the location of single, double, and triple damage scenarios in reinforced concrete (RC) beams are assessed using the Wavelet transform coefficient. To achieve this goal, the numerical models of RC concrete beams were conducted based on the experimental specimens. The mode shapes and corresponding modal curvatures of the RC beam models in damaged and undamaged status were considered as input signals in Wavelet transform. By considering the Wavelet coefficient as damage index, Daubechies, Biorthogonal, and Reverse Biorthogonal Wavelet families were compared to select the most proper one to identify damage locations. Moreover, various sampling distances and their influence on the damage index were studied. In order to simulate the practical situations, two kinds of noises were added to modal data and then denoised by Wavelet analysis to check the proposed damage index in noisy conditions. The results revealed that among the wavelet families, rbio2.4 and rbio2.2 outperform others in detecting damage locations using mode shapes and modal curvatures, respectively. As expected, the sensitivity of modal curvatures to different damage scenarios is more the mode shapes. By increasing sampling distances from 25 mm to 100 mm, the accuracy of the proposed damage index reduces. In order to eliminate boundary effects, it is necessary to use windowing techniques. Applying Wavelet denoising methods on noise-contaminated modal curvatures leads to proper damage localization in both types of noises.
format	article
author	Hashem Jahangir Hamed Hasani Mohammad Reza Esfahani
author_facet	Hashem Jahangir Hamed Hasani Mohammad Reza Esfahani
author_sort	Hashem Jahangir
title	Damage Localization of RC Beams via Wavelet Analysis of Noise Contaminated Modal Curvatures
title_short	Damage Localization of RC Beams via Wavelet Analysis of Noise Contaminated Modal Curvatures
title_full	Damage Localization of RC Beams via Wavelet Analysis of Noise Contaminated Modal Curvatures
title_fullStr	Damage Localization of RC Beams via Wavelet Analysis of Noise Contaminated Modal Curvatures
title_full_unstemmed	Damage Localization of RC Beams via Wavelet Analysis of Noise Contaminated Modal Curvatures
title_sort	damage localization of rc beams via wavelet analysis of noise contaminated modal curvatures
publisher	Pouyan Press
publishDate	2021
url	https://doaj.org/article/ed04cb04639e403a91c615bd997fb357
work_keys_str_mv	AT hashemjahangir damagelocalizationofrcbeamsviawaveletanalysisofnoisecontaminatedmodalcurvatures AT hamedhasani damagelocalizationofrcbeamsviawaveletanalysisofnoisecontaminatedmodalcurvatures AT mohammadrezaesfahani damagelocalizationofrcbeamsviawaveletanalysisofnoisecontaminatedmodalcurvatures
_version_	1718439177920446464

Damage Localization of RC Beams via Wavelet Analysis of Noise Contaminated Modal Curvatures

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