Application of statistical pattern recognition methods for structural damage detection under various ambient conditions

Structural health monitoring is an economical and reliable strategy for infrastructure condition assessment. In recent years, researchers have tried to propose algorithms based on statistical pattern recognition techniques. Studies show these algorithms can be successfully used to detect structural...

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Autores principales:	Fahimeh Jalalifar, mohammad Reza Esfahani, Farzad Shahabian
Formato:	article
Lenguaje:	FA
Publicado:	Iranian Society of Structrual Engineering (ISSE) 2019
Materias:	statistical pattern recognition structural damage detection time history analysis control chart mahalanobis distance Bridge engineering TG1-470 Building construction TH1-9745
Acceso en línea:	https://doaj.org/article/b2a90a0f5e104580ad0223c48b863d01
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spelling	oai:doaj.org-article:b2a90a0f5e104580ad0223c48b863d012021-11-08T15:51:31ZApplication of statistical pattern recognition methods for structural damage detection under various ambient conditions2476-39772538-261610.22065/jsce.2017.97256.1315https://doaj.org/article/b2a90a0f5e104580ad0223c48b863d012019-06-01T00:00:00Zhttps://www.jsce.ir/article_53143_1abb3f4f10082575cdb140c64c4f38d1.pdfhttps://doaj.org/toc/2476-3977https://doaj.org/toc/2538-2616Structural health monitoring is an economical and reliable strategy for infrastructure condition assessment. In recent years, researchers have tried to propose algorithms based on statistical pattern recognition techniques. Studies show these algorithms can be successfully used to detect structural damage. Variability of operational and ambient conditions during data acquisition should be considered as an important factor in applying statistical pattern recognition methods in practical applications. This paper studies the efficiency of statistical pattern recognition methods on the damage detection of structures under various operational and ambient conditions. The data is obtained from an experimental study on an eight degrees of freedom mass spring system. Ambient vibration is applied to the mass spring system using random excitation. In order to simulate various ambient conditions, the amplitude level of the input force has been varied. By applying the statistical pattern recognition methods, the ability of these methods to damage detection under various ambient conditions is discussed. Two common approaches of statistical pattern recognition are considered. These approaches are autoregressive model accompanied with using control chart and Mahalanobis distance for outlier analysis. Results show the importance of considering the statistical pattern recognition methods for structural damage detection under various operational and ambient conditions.Fahimeh Jalalifarmohammad Reza EsfahaniFarzad ShahabianIranian Society of Structrual Engineering (ISSE)articlestatistical pattern recognitionstructural damage detectiontime history analysiscontrol chartmahalanobis distanceBridge engineeringTG1-470Building constructionTH1-9745FAJournal of Structural and Construction Engineering, Vol 6, Iss 1, Pp 85-97 (2019)
institution	DOAJ
collection	DOAJ
language	FA
topic	statistical pattern recognition structural damage detection time history analysis control chart mahalanobis distance Bridge engineering TG1-470 Building construction TH1-9745
spellingShingle	statistical pattern recognition structural damage detection time history analysis control chart mahalanobis distance Bridge engineering TG1-470 Building construction TH1-9745 Fahimeh Jalalifar mohammad Reza Esfahani Farzad Shahabian Application of statistical pattern recognition methods for structural damage detection under various ambient conditions
description	Structural health monitoring is an economical and reliable strategy for infrastructure condition assessment. In recent years, researchers have tried to propose algorithms based on statistical pattern recognition techniques. Studies show these algorithms can be successfully used to detect structural damage. Variability of operational and ambient conditions during data acquisition should be considered as an important factor in applying statistical pattern recognition methods in practical applications. This paper studies the efficiency of statistical pattern recognition methods on the damage detection of structures under various operational and ambient conditions. The data is obtained from an experimental study on an eight degrees of freedom mass spring system. Ambient vibration is applied to the mass spring system using random excitation. In order to simulate various ambient conditions, the amplitude level of the input force has been varied. By applying the statistical pattern recognition methods, the ability of these methods to damage detection under various ambient conditions is discussed. Two common approaches of statistical pattern recognition are considered. These approaches are autoregressive model accompanied with using control chart and Mahalanobis distance for outlier analysis. Results show the importance of considering the statistical pattern recognition methods for structural damage detection under various operational and ambient conditions.
format	article
author	Fahimeh Jalalifar mohammad Reza Esfahani Farzad Shahabian
author_facet	Fahimeh Jalalifar mohammad Reza Esfahani Farzad Shahabian
author_sort	Fahimeh Jalalifar
title	Application of statistical pattern recognition methods for structural damage detection under various ambient conditions
title_short	Application of statistical pattern recognition methods for structural damage detection under various ambient conditions
title_full	Application of statistical pattern recognition methods for structural damage detection under various ambient conditions
title_fullStr	Application of statistical pattern recognition methods for structural damage detection under various ambient conditions
title_full_unstemmed	Application of statistical pattern recognition methods for structural damage detection under various ambient conditions
title_sort	application of statistical pattern recognition methods for structural damage detection under various ambient conditions
publisher	Iranian Society of Structrual Engineering (ISSE)
publishDate	2019
url	https://doaj.org/article/b2a90a0f5e104580ad0223c48b863d01
work_keys_str_mv	AT fahimehjalalifar applicationofstatisticalpatternrecognitionmethodsforstructuraldamagedetectionundervariousambientconditions AT mohammadrezaesfahani applicationofstatisticalpatternrecognitionmethodsforstructuraldamagedetectionundervariousambientconditions AT farzadshahabian applicationofstatisticalpatternrecognitionmethodsforstructuraldamagedetectionundervariousambientconditions
_version_	1718441695457050624

Application of statistical pattern recognition methods for structural damage detection under various ambient conditions

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