System identification and model updating of a steel cantilever beam using vibration tests. Sabamehr, A., Bagchi, A., Tirca, L., Panigrahi, S., & Chourasia, A. In pages 198 - 201, Ingolstadt, Germany, 2017. Frequency domain decomposition;Modal parameters;Modal properties;Model updating;Real structure;Stochastic subspace identification;Structural health monitoring (SHM);Vibration response;abstract bibtex Structural Health Monitoring (SHM) based on vibration-based techniques have attracted significant attention in the past. Many of the methods rely on appropriate Finite Element (FE) or other mathematical model of a structure and updating the model using the field data. The measured response of a structure and the results from its FE model may have some differences due for many factors including, potential construction deviation, differences in actual material properties from that assumed in the model, complicated connections that is different from the idealized ones used in the model, etc. Model updating method is used to correlate an FE model to the real structure using its measured response. Here, two common techniques, namely, Frequency Domain Decomposition and Data-Driven Stochastic Subspace Identification have been used to identify the modal properties of a steel cantilever beam based on its measured vibration response. Based on the identified modal parameters, an FE model of the structure is updated using two different types of procedures, such as, matrix update method, which is physics-based and neural networks method, which is data-driven. It is observed that the quality of the experimental data affects the performance of these methods.
@inproceedings{20173103999873 ,
language = {English},
copyright = {Compilation and indexing terms, Copyright 2023 Elsevier Inc.},
copyright = {Compendex},
title = {System identification and model updating of a steel cantilever beam using vibration tests},
journal = {IOMAC 2017 - 7th International Operational Modal Analysis Conference},
author = {Sabamehr, A. and Bagchi, A. and Tirca, L. and Panigrahi, S.K. and Chourasia, A.},
year = {2017},
pages = {198 - 201},
address = {Ingolstadt, Germany},
abstract = {Structural Health Monitoring (SHM) based on vibration-based techniques have attracted significant attention in the past. Many of the methods rely on appropriate Finite Element (FE) or other mathematical model of a structure and updating the model using the field data. The measured response of a structure and the results from its FE model may have some differences due for many factors including, potential construction deviation, differences in actual material properties from that assumed in the model, complicated connections that is different from the idealized ones used in the model, etc. Model updating method is used to correlate an FE model to the real structure using its measured response. Here, two common techniques, namely, Frequency Domain Decomposition and Data-Driven Stochastic Subspace Identification have been used to identify the modal properties of a steel cantilever beam based on its measured vibration response. Based on the identified modal parameters, an FE model of the structure is updated using two different types of procedures, such as, matrix update method, which is physics-based and neural networks method, which is data-driven. It is observed that the quality of the experimental data affects the performance of these methods.<br/>},
key = {Identification (control systems)},
keywords = {Frequency domain analysis;Modal analysis;Nanocantilevers;Structural health monitoring;Stochastic systems;Cantilever beams;Domain decomposition methods;Finite element method;Religious buildings;},
note = {Frequency domain decomposition;Modal parameters;Modal properties;Model updating;Real structure;Stochastic subspace identification;Structural health monitoring (SHM);Vibration response;},
}
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