IDENTIFICATION OF MODAL PARAMETERS OF VIBRATING STRUCTURES WITH UNKNOWN ORSTOCHASTIC EXCITATION
The Vector Autoregressive Moving Average (VARMA) Model is used to identify dynamical characteristics of a structural system in the presence of noise. In order to estimate the parameters of the VARMA Model, the Spliid’s fast algorithm is used. To determine the modal parameters the companion matrix is...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2005 |
| País: | Perú |
| Institución: | Universidad Nacional Mayor de San Marcos |
| Repositorio: | Revistas - Universidad Nacional Mayor de San Marcos |
| Idioma: | español |
| OAI Identifier: | oai:revistasinvestigacion.unmsm.edu.pe:article/6186 |
| Acceso en línea: | https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/6186 |
| Access Level: | acceso abierto |
| Palabra clave: | VARMA modal analysis companion matrix multivariate estimation. análisis modal matriz compañera multivariado estimación mantenimento preventivo. |
| Sumario: | The Vector Autoregressive Moving Average (VARMA) Model is used to identify dynamical characteristics of a structural system in the presence of noise. In order to estimate the parameters of the VARMA Model, the Spliid’s fast algorithm is used. To determine the modal parameters the companion matrix is built with the autoregressive part of the VARMA Model. The performance of this method here discussed is presented by means of simulations, using three degrees of freedom mass-dampingstiffness vibrating system. |
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