Littérature scientifique sur le sujet « Model Updating, Structural Health Monitoring »
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Articles de revues sur le sujet "Model Updating, Structural Health Monitoring"
Haidarpour, Amirabbas, et Kong Fah Tee. « Finite Element Model Updating for Structural Health Monitoring ». Structural Durability & ; Health Monitoring 14, no 1 (2020) : 1–17. http://dx.doi.org/10.32604/sdhm.2020.08792.
Texte intégralRocchetta, Roberto, Matteo Broggi, Quentin Huchet et Edoardo Patelli. « On-line Bayesian model updating for structural health monitoring ». Mechanical Systems and Signal Processing 103 (mars 2018) : 174–95. http://dx.doi.org/10.1016/j.ymssp.2017.10.015.
Texte intégralDan, Danhui, Tong Yang et Jiongxin Gong. « Intelligent Platform for Model Updating in a Structural Health Monitoring System ». Mathematical Problems in Engineering 2014 (2014) : 1–11. http://dx.doi.org/10.1155/2014/628619.
Texte intégralSchommer, Sebastian, Viet Ha Nguyen, Stefan Maas et Arno Zürbes. « Model updating for structural health monitoring using static and dynamic measurements ». Procedia Engineering 199 (2017) : 2146–53. http://dx.doi.org/10.1016/j.proeng.2017.09.156.
Texte intégralDey, Palash, V. Akhil et A. I. Laskar. « Application of Smartphone and Model Updating Technique in Structural Health Monitoring ». Arabian Journal for Science and Engineering 44, no 5 (28 septembre 2018) : 4819–28. http://dx.doi.org/10.1007/s13369-018-3565-8.
Texte intégralChing, Jianye, Matthew Muto et James L. Beck. « Structural Model Updating and Health Monitoring with Incomplete Modal Data Using Gibbs Sampler ». Computer-Aided Civil and Infrastructure Engineering 21, no 4 (mai 2006) : 242–57. http://dx.doi.org/10.1111/j.1467-8667.2006.00432.x.
Texte intégralBetti, Michele, Salvatore Giacomo Morano, Gianni Bartoli, Giacomo Zini et Paolo Spinelli. « Structural health monitoring of a masonry arch bridge : modal identification and model updating ». International Journal of Masonry Research and Innovation 1, no 1 (2022) : 1. http://dx.doi.org/10.1504/ijmri.2022.10052514.
Texte intégralYang, J., H. F. Lam et J. Hu. « Ambient Vibration Test, Modal Identification and Structural Model Updating Following Bayesian Framework ». International Journal of Structural Stability and Dynamics 15, no 07 (31 août 2015) : 1540024. http://dx.doi.org/10.1142/s0219455415400246.
Texte intégralMordini, Andrea, Konstantin Savov et Helmut Wenzel. « The Finite Element Model Updating : A Powerful Tool for Structural Health Monitoring ». Structural Engineering International 17, no 4 (novembre 2007) : 352–58. http://dx.doi.org/10.2749/101686607782359010.
Texte intégralChing, Jianye, et James L. Beck. « New Bayesian Model Updating Algorithm Applied to a Structural Health Monitoring Benchmark ». Structural Health Monitoring : An International Journal 3, no 4 (décembre 2004) : 313–32. http://dx.doi.org/10.1177/1475921704047499.
Texte intégralThèses sur le sujet "Model Updating, Structural Health Monitoring"
Kodikara, Kodikara Arachchige Tharindu Lakshitha. « Structural health monitoring through advanced model updating incorporating uncertainties ». Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/110811/1/Kodikara%20Arachchige%20Tharindu%20Lakshitha_Kodikara_Thesis.pdf.
Texte intégralMoravej, Hans. « Vibration-based probabilistic model updating of civil structures using structural health monitoring techniques ». Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/203653/1/Hans%20Moravej%20Thesis.pdf.
Texte intégralSmith, Chandler B. « Sparsity Constrained Inverse Problems - Application to Vibration-based Structural Health Monitoring ». ScholarWorks @ UVM, 2019. https://scholarworks.uvm.edu/graddis/1143.
Texte intégralZolghadri, Navid. « Short and Long-Term Structural Health Monitoring of Highway Bridges ». DigitalCommons@USU, 2017. https://digitalcommons.usu.edu/etd/5626.
Texte intégralLee, Soon Gie. « Hybrid Damage Identification Based on Wavelet Transform and Finite Element Model Updating ». University of Akron / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=akron1333676433.
Texte intégralAREZZO, DAVIDE. « An innovative framework for Vibration Based Structural Health Monitoring of buildings through Artificial Intelligence approaches ». Doctoral thesis, Università Politecnica delle Marche, 2022. http://hdl.handle.net/11566/299822.
Texte intégralStructural health monitoring consists of identifying all those processes aimed at assessing the safety of a structure. These processes found their first application in the field of aerospace and mechanical engineering in order to assess the performance and occurrence of damage in mechanical components of vehicles and rotating industrial machinery. Over time, the need to assess the health status of structures has also led to the use of these techniques in the field of civil engineering, in particular vibration-based monitoring through the application of Operational Modal Analysis (OMA) techniques. These techniques are well established, based on solid theoretical foundations, and implemented in numerous frameworks for structural health monitoring. However, the definition and implementation of an effective dynamic monitoring capable to detect damage requires a high degree of multi-disciplinary and the contribution of specialists from different fields, i.e., measurement engineering, computer science, electronic engineering, dynamic identification, structural engineering, data science. During the PhD activities an effort have been made for the development of a framework for Vibration-Based Structural Health Monitoring system (VB-SHM) in all its part, attempting to achieve replicability of the system and its effectiveness in correctly tracking the health conditions of the structure over time. Replicability is crucial to promote the widest possible spread of this kind of monitoring. The framework has been developed starting from results obtained by three main case studies monitored during the PhD activities. The case study of the Santa Maria in Via Church in Camerino deal with the problem of dynamic identification, model updating and optimal sensor placement. Due to the complexity of the finite element model, model updating has been carried out with the aid of Particle Swarm Optimization algorithm. Thereafter, monitoring results of the r.c. school building in Camerino monitored during the 2016 seismic sequence are presented. Throughout the monitoring period, the response of the building to several low to medium intensity earthquakes was recorded. The building, despite the absence of damage, showed a time-varying dynamic behaviour making it difficult to track the frequencies during the seismic response. By applying a linearisation procedure, frequencies are tracked even during strong motions. Finally, the monitoring results of the Engineering Tower of the Università Politecnica delle Marche are reported. The Tower has been monitored since 2017 and, although with some interruptions, allowed the observation of a marked dependence of its eigen-frequencies on environmental parameters, especially temperature and wind. These effects have been effectively cleansed through the implementation of an artificial neural network.
Shiki, Sidney Bruce [UNESP]. « Application of Volterra series in nonlinear mechanical system identification and in structural health monitoring problems ». Universidade Estadual Paulista (UNESP), 2016. http://hdl.handle.net/11449/137761.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Estruturas com comportamento não-linear são frequentes em dinâmica estrutural, principalmente considerando componentes parafusados, com juntas, folgas ou estruturas flexíveis sujeitas à grandes deslocamentos. Desse modo, o monitoramento de estruturas com métodos lineares clássicos, como os baseados em parâmetros modais, podem falhar drasticamente em caracterizar efeitos não-lineares. Neste trabalho foi proposta a utilização de séries de Volterra para identificação de sistemas mecânicos não-lineares em aplicações de detecção de danos e quantificação de parâmetros. A propriedade deste modelo de representar separadamente os componentes de resposta linear e não-linear do sistema foi aplicada para se construir índices de dano que evidenciam a necessidade de modelagem não-linear. Além disso métricas de resíduo linear e não-linear dos termos do modelo de Volterra são empregadas para identificar modelos paramétricos da estrutura. As metodologias propostas são ilustradas em bancadas experimentais de modo a evidenciar a importância de fenômenos não-lineares para o monitoramento de estruturas.
Nonlinear structures are frequent in structural dynamics, specially considering screwed components, with joints, clearance or flexible components presenting large displacements. In this sense the monitoring of systems based on classical linear methods, as the ones based on modal parameters, can drastically fail to characterize nonlinear effects. This thesis proposed the use of Volterra series for nonlinear system identification aiming applications in damage detection and parameter quantification. The property of this model of representing the linear and nonlinear components of the response of a system was used to formulate damage features to make clear the need of nonlinear modeling. Also metrics based on the linear and nonlinear residues of the terms of the Volterra model were employed to identify parametric models of the structure. The proposed methodologies are illustrated in experimental setups to show the relevance of nonlinear phenomena in the structural health monitoring.
FAPESP: 2012/04757-6
FAPESP: 2013/25148-0
FAPESP: 2012/21195-1
FAPESP: 2015/03560-2
Shiki, Sidney Bruce. « Application of Volterra series in nonlinear mechanical system identification and in structural health monitoring problems / ». Ilha Solteira, 2016. http://hdl.handle.net/11449/137761.
Texte intégralAbstract: Nonlinear structures are frequent in structural dynamics, specially considering screwed components, with joints, clearance or flexible components presenting large displacements. In this sense the monitoring of systems based on classical linear methods, as the ones based on modal parameters, can drastically fail to characterize nonlinear effects. This thesis proposed the use of Volterra series for nonlinear system identification aiming applications in damage detection and parameter quantification. The property of this model of representing the linear and nonlinear components of the response of a system was used to formulate damage features to make clear the need of nonlinear modeling. Also metrics based on the linear and nonlinear residues of the terms of the Volterra model were employed to identify parametric models of the structure. The proposed methodologies are illustrated in experimental setups to show the relevance of nonlinear phenomena in the structural health monitoring.
Resumo: Estruturas com comportamento não-linear são frequentes em dinâmica estrutural, principalmente considerando componentes parafusados, com juntas, folgas ou estruturas flexíveis sujeitas à grandes deslocamentos. Desse modo, o monitoramento de estruturas com métodos lineares clássicos, como os baseados em parâmetros modais, podem falhar drasticamente em caracterizar efeitos não-lineares. Neste trabalho foi proposta a utilização de séries de Volterra para identificação de sistemas mecânicos não-lineares em aplicações de detecção de danos e quantificação de parâmetros. A propriedade deste modelo de representar separadamente os componentes de resposta linear e não-linear do sistema foi aplicada para se construir índices de dano que evidenciam a necessidade de modelagem não-linear. Além disso métricas de resíduo linear e não-linear dos termos do modelo de Volterra são empregadas para identificar modelos paramétricos da estrutura. As metodologias propostas são ilustradas em bancadas experimentais de modo a evidenciar a importância de fenômenos não-lineares para o monitoramento de estruturas.
Doutor
Al, Jailawi Samer Saadi Hussein. « Damage detection using angular velocity ». Diss., University of Iowa, 2018. https://ir.uiowa.edu/etd/6539.
Texte intégralWang, Liang. « Innovative damage assessment of steel truss bridges using modal strain energy correlation ». Thesis, Queensland University of Technology, 2012. https://eprints.qut.edu.au/53177/1/Liang_Wang_Thesis.pdf.
Texte intégralLivres sur le sujet "Model Updating, Structural Health Monitoring"
Feng, Maria Q. Long-term structural performance monitoring of bridges : Development of baseline model and methodology for health monitoring and damage assessment. Sacramento, Calif : California Dept. of Transportation, Division of Research and Innovation, 2008.
Trouver le texte intégralChapitres de livres sur le sujet "Model Updating, Structural Health Monitoring"
Soyoz, Serdar. « Model Updating Techniques for Structures Under Seismic Excitation ». Dans Seismic Structural Health Monitoring, 199–216. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13976-6_8.
Texte intégralSehgal, Shankar, et Harmesh Kumar. « Damage Detection Using Derringer’s Function based Weighted Model Updating Method ». Dans Structural Health Monitoring, Volume 5, 241–53. Cham : Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04570-2_27.
Texte intégralCarroll, Michael, Austin Downey, Jacob Dodson, Jonathan Hong et James Scheppegrell. « Subsecond Model Updating for High-Rate Structural Health Monitoring ». Dans Topics in Modal Analysis & ; Testing, Volume 8, 201–6. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47717-2_19.
Texte intégralZhu, Yi-Chen, David Wagg, Elizabeth Cross et Robert Barthorpe. « Real-Time Digital Twin Updating Strategy Based on Structural Health Monitoring Systems ». Dans Model Validation and Uncertainty Quantification, Volume 3, 55–64. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47638-0_6.
Texte intégralHeo, Gwang Hee, Joon Ryong Jeon, Chin Ok Lee, Gui Lee et Woo Sang Lee. « FE Model Updating for Health Monitoring of Structures and its Experimental Verification by Damage Detection ». Dans Advanced Nondestructive Evaluation I, 268–72. Stafa : Trans Tech Publications Ltd., 2006. http://dx.doi.org/10.4028/0-87849-412-x.268.
Texte intégralDe Roeck, Guido. « Model–Based Methods of Damage Identification of Structures Under Seismic Excitation ». Dans Seismic Structural Health Monitoring, 237–59. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13976-6_10.
Texte intégralXu, Y. F., W. D. Zhu, J. Liu et Y. M. Shao. « Non-Model-Based Crack Identification Using Measured Mode Shapes ». Dans Structural Health Monitoring, Volume 5, 279–97. Cham : Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04570-2_31.
Texte intégralGallina, Alberto, Paweł Paćko et Łukasz Ambroziński. « Model Assisted Probability of Detection in Structural Health Monitoring ». Dans Advanced Structural Damage Detection, 57–72. Chichester, UK : John Wiley & Sons, Ltd, 2013. http://dx.doi.org/10.1002/9781118536148.ch3.
Texte intégralDonajkowski, Hannah, Salma Leyasi, Gregory Mellos, Chuck R. Farrar, Alex Scheinker, Jin-Song Pei et Nicholas A. J. Lieven. « Comparison of Complexity Measures for Structural Health Monitoring ». Dans Model Validation and Uncertainty Quantification, Volume 3, 27–39. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47638-0_3.
Texte intégralFinzi Neto, Roberto Mendes, et Jose dos Reis Vieira de Moura. « Fundamental Concepts for Impedance-based Structural Health Monitoring ». Dans Model-based and Signal-Based Inverse Methods, 443–71. Brasilia : Biblioteca Central da Universidade de Brasilia, 2022. http://dx.doi.org/10.4322/978-65-86503-71-5.c12.
Texte intégralActes de conférences sur le sujet "Model Updating, Structural Health Monitoring"
IGEA, FELIPE, MANOLIS N. CHATZIS et ALICE CICIRELLO. « STRUCTURAL MODEL UPDATING USING VARIATIONAL INFERENCE ». Dans Structural Health Monitoring 2021. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/shm2021/36282.
Texte intégralZENG, JICE, YOUNG HOON HOON KIM et SHIQIANG QIN. « BAYESIAN MODEL UPDATING FOR A CABLE-STAYED PEDESTRIAN BRIDGE USING DREAM AND KRIGING MODEL ». Dans Structural Health Monitoring 2021. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/shm2021/36256.
Texte intégralBRUNS, MARLENE, BENEDIKT HOFMEISTER, CLEMENS HÜBLER et RAIMUND ROLFES. « Damage Localization Via Model Updating Using a Damage Distribution Function ». Dans Structural Health Monitoring 2019. Lancaster, PA : DEStech Publications, Inc., 2019. http://dx.doi.org/10.12783/shm2019/32202.
Texte intégralSIMPSON, THOMAS, VASILIS DERTIMANIS, COSTAS PAPADIMITRIOU et ELENI CHATZI. « On the Potential of Dynamic Sub-structuring Methods for Model Updating ». Dans Structural Health Monitoring 2019. Lancaster, PA : DEStech Publications, Inc., 2019. http://dx.doi.org/10.12783/shm2019/32500.
Texte intégralHUANG, YONG, JAMES L. BECK et HUI LI. « Multi-Task Sparse Bayesian Learning For Model Updating In Structural Health Monitoring ». Dans Structural Health Monitoring 2017. Lancaster, PA : DEStech Publications, Inc., 2017. http://dx.doi.org/10.12783/shm2017/14097.
Texte intégralKERNICKY, TIMOTHY, MATTHEW WHELAN, USMAN RAUF et EHAB AL-SHAER. « Damage Detection in a Laboratory Model Using a Nonlinear Constraint Satisfaction Processor for Finite Element Model Updating ». Dans Structural Health Monitoring 2015. Destech Publications, 2015. http://dx.doi.org/10.12783/shm2015/175.
Texte intégralFANG, ZHIHONG, JINGYU HUANG, XIAONONG WANG, LIANG ZHAO, SHUOWEI WANG, ZIYANG ZHANG et DEXIANG LI. « RESEARCH ON MODEL UPDATING METHOD OF HIGH- SPEED MAGLEV GUIDEWAY BASED ON WAVELET TRANSFORM AND OPTIMIZATION ALGORITHM ». Dans Structural Health Monitoring 2021. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/shm2021/36290.
Texte intégralSABAMEHR, ARDALAN, CHAEWOON LIM et ASHUTOSH BAGCHI. « Updating the Mathematical Models of Bridges Using Data-driven Techniques ». Dans Structural Health Monitoring 2015. Destech Publications, 2015. http://dx.doi.org/10.12783/shm2015/156.
Texte intégralSCHRODER, KARSTEN, et RAIMUND ROLFES. « Application of a Finite Element Model Updating Approach to Damage Localization at Offshore Wind Energy Converters ». Dans Structural Health Monitoring 2015. Destech Publications, 2015. http://dx.doi.org/10.12783/shm2015/341.
Texte intégralEreiz, Suzana, et Ivan Duvnjak. « Hybrid model updating based on structural health monitoring in structural dynamics ». Dans 6th Symposium on Doctoral Studies in Civil Engineering. University of Zagreb Faculty of Civil Engineering, 2019. http://dx.doi.org/10.5592/co/phdsym.2020.10.
Texte intégralRapports d'organisations sur le sujet "Model Updating, Structural Health Monitoring"
Taylor, Stuart G. A Multi-scale Approach to Statistical and Model-based Structural Health Monitoring with Application to Embedded Sensing for Wind Energy. Office of Scientific and Technical Information (OSTI), janvier 2013. http://dx.doi.org/10.2172/1059871.
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