Optimal sensor placement for structural parameter identification of bridges with modeling uncertainties
The uncertainties in the numerical models used for the optimal sensor placement (OSP) studies of civil infrastructures, specifically bridges, considerably affect the results. These effects can be more prominent if the modeling uncertainties are of a kind that significantly alters the mode shapes of...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/394637 |
| Acceso en línea: | https://hdl.handle.net/2117/394637 https://dx.doi.org/10.1016/j.engstruct.2023.116561 |
| Access Level: | acceso abierto |
| Palabra clave: | Structural health monitoring Railroad bridges Optimal sensor locations Monte Carlo simulation Modal identification Effective independence Hierarchical clustering Model uncertainty Railway bridges Monitorització de salut estructural Ponts de ferrocarril Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Tipologies estructurals |
| Sumario: | The uncertainties in the numerical models used for the optimal sensor placement (OSP) studies of civil infrastructures, specifically bridges, considerably affect the results. These effects can be more prominent if the modeling uncertainties are of a kind that significantly alters the mode shapes of the structure, such as the boundary conditions of the model. Yet, these effects on the results of OSP analysis remain unexplored, and there are no available methodologies to address all types of model uncertainties in OSP for civil infrastructures. This research presents a new framework to determine the optimal sensor locations to identify the modal properties of bridges under severe modeling uncertainties and its application on a railway bridge. The framework includes finite element model generation and a sensitivity study to select the most influential parameters that change the dynamic response of the bridge. The selected parameters are used in Monte Carlo simulations, and the results enable quantifying the relative amount of information presented at the candidate sensor locations. This information is combined with the spatial position of the candidate sensor locations, and a hierarchical clustering algorithm is used to obtain the optimal sensor locations and the number of sensors. In addition, the OSP analysis is carried out using the Effective Independence method to contribute to the state-of-the-art literature that investigates the uncertainties in OSP for civil infrastructures and uses this method. |
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