Estimation of modal parameters of structures subjected to known base accelerations: Application to shake table tests

This paper presents a state space model along with a maximum likelihood algorithm to extract the modal parameters of structures when the vibrations are caused by ground accelerations and these accelerations are recorded. Shake table tests are well-known examples of these situations, but not the only ones. It is shown that in these cases the state space model used to compute the modal parameters is different from the conventional input–output model. Moreover, the proposed model consists of a set of equations that are the same regardless of whether absolute accelerations or relative displacements are used as output data. This is especially important in shake table tests because it is common to use different type of sensors, so it is suggested to exploit the above-mentioned fact to assess the consistency and reliability of the measurements obtained from different instruments (i.e. accelerometers and displacement transducers). The proposed model is estimated using the EM algorithm because the estimates are unbiased and with minimum variance. But the great advantage of this approach is that the EM algorithm can be adapted to estimate different models, in particular the one developed in this work. Finally, the proposed method (model and estimation algorithm) is applied to the experimental data measured during the shake table tests conducted on a reinforced concrete structure.

Authors

Publication Details

Journal
Soil Dynamics and Earthquake Engineering
Published
2025-04-19
DOI
https://doi.org/10.1016/j.soildyn.2025.109437
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Estimation of modal parameters of structures subjected to known base accelerations: Application to shake table tests

Javier Cara, Amadeo Benavent‐Climent, David Escolano‐Margarit
Soil Dynamics and Earthquake Engineering
Structural Health Monitoring Techniques
article

Estimation of modal parameters of structures subjected to known base accelerations: Application to shake table tests

Javier Cara, Amadeo Benavent‐Climent, David Escolano‐Margarit
article en

Abstract

This paper presents a state space model along with a maximum likelihood algorithm to extract the modal parameters of structures when the vibrations are caused by ground accelerations and these accelerations are recorded. Shake table tests are well-known examples of these situations, but not the only ones. It is shown that in these cases the state space model used to compute the modal parameters is different from the conventional input–output model. Moreover, the proposed model consists of a set of equations that are the same regardless of whether absolute accelerations or relative displacements are used as output data. This is especially important in shake table tests because it is common to use different type of sensors, so it is suggested to exploit the above-mentioned fact to assess the consistency and reliability of the measurements obtained from different instruments (i.e. accelerometers and displacement transducers). The proposed model is estimated using the EM algorithm because the estimates are unbiased and with minimum variance. But the great advantage of this approach is that the EM algorithm can be adapted to estimate different models, in particular the one developed in this work. Finally, the proposed method (model and estimation algorithm) is applied to the experimental data measured during the shake table tests conducted on a reinforced concrete structure.

Soil Dynamics and Earthquake EngineeringVol. 196
Agencia Estatal de Investigación
Openalex Percentile: Top 92%
Structural Health Monitoring Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.