Documents disponibles écrits par cet auteur

Ambient vibration data analysis for structural identification and global condition assessment / Mustafa Gul in Journal of engineering mechanics, Vol. 134 n°8 (Août 2008) 

Public ISBD [article]  in Journal of engineering mechanics > Vol. 134 n°8 (Août 2008) . - pp. 650-662 Titre : Ambient vibration data analysis for structural identification and global condition assessment Type de document : texte imprimé Auteurs : Mustafa Gul, Auteur ; F. Necati Catbas, Auteur Année de publication : 2008 Article en page(s) : pp. 650-662 Note générale : Mécanique appliquée Langues : Anglais (eng) Mots-clés : Structural  dynamics  Vibration  Impact  tests  Modal  analysis  Flexibility  Damage. Résumé : System identification is an area which deals with developing mathematical models to characterize the input-output behavior of an unknown system by means of experimental data. Structural health monitoring (SHM) provides the tools and technologies to collect and analyze input and output data to track the structural behavior. One of the most commonly used SHM technologies is dynamic testing. Ambient vibration testing is a practical dynamic testing method especially for large civil structures where input excitation cannot be directly measured. This paper presents a conceptual and reliable methodology for system identification and structural condition assessment using ambient vibration data where input data are not available. The system identification methodology presented in this study is based on the use of complex mode indicator functions (CMIFs) coupled with the random decrement (RD) method to identify the modal parameters from the output only data sets. CMIF is employed for parameter identification from the unscaled multiple-input multiple-output data sets generated using the RD method. For condition assessment, unscaled flexibility and the deflection profiles obtained from the dynamic tests are presented as a conceptual indicator. Laboratory tests on a steel grid and field tests on a long-span bridge were conducted and the dynamic properties identified from these tests are presented. For demonstrating condition assessment, deflected shapes obtained from unscaled flexibility are compared for undamaged and damaged laboratory grid structures. It is shown that structural changes on the steel grid structure are identified by using the unscaled deflected shapes. ISSN : 0733-9399 En ligne : http://cedb.asce.org/cgi/WWWdisplay.cgi?166079 [article] Ambient vibration data analysis for structural identification and global condition assessment [texte imprimé] / Mustafa Gul, Auteur ; F. Necati Catbas, Auteur . - 2008 . - pp. 650-662. Mécanique appliquée Langues : Anglais (eng) in Journal of engineering mechanics > Vol. 134 n°8 (Août 2008) . - pp. 650-662 Mots-clés : Structural  dynamics  Vibration  Impact  tests  Modal  analysis  Flexibility  Damage. Résumé : System identification is an area which deals with developing mathematical models to characterize the input-output behavior of an unknown system by means of experimental data. Structural health monitoring (SHM) provides the tools and technologies to collect and analyze input and output data to track the structural behavior. One of the most commonly used SHM technologies is dynamic testing. Ambient vibration testing is a practical dynamic testing method especially for large civil structures where input excitation cannot be directly measured. This paper presents a conceptual and reliable methodology for system identification and structural condition assessment using ambient vibration data where input data are not available. The system identification methodology presented in this study is based on the use of complex mode indicator functions (CMIFs) coupled with the random decrement (RD) method to identify the modal parameters from the output only data sets. CMIF is employed for parameter identification from the unscaled multiple-input multiple-output data sets generated using the RD method. For condition assessment, unscaled flexibility and the deflection profiles obtained from the dynamic tests are presented as a conceptual indicator. Laboratory tests on a steel grid and field tests on a long-span bridge were conducted and the dynamic properties identified from these tests are presented. For demonstrating condition assessment, deflected shapes obtained from unscaled flexibility are compared for undamaged and damaged laboratory grid structures. It is shown that structural changes on the steel grid structure are identified by using the unscaled deflected shapes. ISSN : 0733-9399 En ligne : http://cedb.asce.org/cgi/WWWdisplay.cgi?166079

Damage assessment with ambient vibration data using a novel time series analysis methodology / Mustafa Gul in Journal of structural engineering, Vol. 137 N° 12 (Décembre 2011) 

Public ISBD [article]  in Journal of structural engineering > Vol. 137 N° 12 (Décembre 2011) . - pp. 1518-1526 Titre : Damage assessment with ambient vibration data using a novel time series analysis methodology Type de document : texte imprimé Auteurs : Mustafa Gul, Auteur ; F. Necati Catbas, Auteur Année de publication : 2012 Article en page(s) : pp. 1518-1526 Note générale : Génie Civil Langues : Anglais (eng) Mots-clés : Structural  health  monitoring  Damage  detection  Time  series  analysis  Statistical  pattern  recognition  Ambient  vibration  Bridge  Identification Résumé : In this study, a novel approach using a modified time series analysis methodology is used to detect and locate structural changes by using ambient vibration data. In addition, it is shown that the level of the damage feature gives important information about the relative change of the damage severity, although direct damage quantification is not achieved. In this methodology, random decrement (RD) is used to obtain pseudofree response data from the ambient vibration time histories. Autoregressive models with exogenous input (ARX models) are created for different sensor clusters by using the pseudofree response of the structure. The output of each sensor in a cluster is used as an input to the ARX model to predict the output of the reference channel of that sensor cluster. After creating ARX models for the healthy structure for each sensor cluster, these models are used for predicting the data from the damaged structure. The difference between the fit ratios is used as the damage feature. The methodology is first applied to experimental ambient vibration data from a steel grid structure, in which different damage scenarios, such as local stiffness loss and boundary condition change, are simulated. The results show that damage was detected and located successfully for most of these cases. Moreover, it is observed that the relative extent of the damage is also estimated by using the method. Then, output-only data from the Z24 bridge is used for further verification of the methodology with real-life data where different levels of pier settlement were applied as damage. It is shown that the approach is successful in damage identification and localization with a minimum number of false alarms. The potential and advantages of the methodology are discussed on the basis of the experimental results. Limitations of the approach are also addressed, along with future research directions. DEWEY : 624.17 ISSN : 0733-9445 En ligne : http://ascelibrary.org/sto/resource/1/jsendh/v137/i12/p1518_s1?isAuthorized=no [article] Damage assessment with ambient vibration data using a novel time series analysis methodology [texte imprimé] / Mustafa Gul, Auteur ; F. Necati Catbas, Auteur . - 2012 . - pp. 1518-1526. Génie Civil Langues : Anglais (eng) in Journal of structural engineering > Vol. 137 N° 12 (Décembre 2011) . - pp. 1518-1526 Mots-clés : Structural  health  monitoring  Damage  detection  Time  series  analysis  Statistical  pattern  recognition  Ambient  vibration  Bridge  Identification Résumé : In this study, a novel approach using a modified time series analysis methodology is used to detect and locate structural changes by using ambient vibration data. In addition, it is shown that the level of the damage feature gives important information about the relative change of the damage severity, although direct damage quantification is not achieved. In this methodology, random decrement (RD) is used to obtain pseudofree response data from the ambient vibration time histories. Autoregressive models with exogenous input (ARX models) are created for different sensor clusters by using the pseudofree response of the structure. The output of each sensor in a cluster is used as an input to the ARX model to predict the output of the reference channel of that sensor cluster. After creating ARX models for the healthy structure for each sensor cluster, these models are used for predicting the data from the damaged structure. The difference between the fit ratios is used as the damage feature. The methodology is first applied to experimental ambient vibration data from a steel grid structure, in which different damage scenarios, such as local stiffness loss and boundary condition change, are simulated. The results show that damage was detected and located successfully for most of these cases. Moreover, it is observed that the relative extent of the damage is also estimated by using the method. Then, output-only data from the Z24 bridge is used for further verification of the methodology with real-life data where different levels of pier settlement were applied as damage. It is shown that the approach is successful in damage identification and localization with a minimum number of false alarms. The potential and advantages of the methodology are discussed on the basis of the experimental results. Limitations of the approach are also addressed, along with future research directions. DEWEY : 624.17 ISSN : 0733-9445 En ligne : http://ascelibrary.org/sto/resource/1/jsendh/v137/i12/p1518_s1?isAuthorized=no