Joint input-state estimation in structural dynamics

Maes, Kristof; Smyth, Andrew W.; Roeck, Guido De; Lombaert, Geert

doi:10.1016/j.ymssp.2015.07.025

Cited by 110 publications

(100 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Section 2.1 first gives a brief summary of the joint input-state estimation algorithm introduced in [26]. Next, Section 2.2 describes the approach for quantification of the estimation uncertainty originating from measurement errors and unknown stochastic excitation presented in [26].…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…Next, Section 2.2 describes the approach for quantification of the estimation uncertainty originating from measurement errors and unknown stochastic excitation presented in [26]. This approach is applied in this paper to quantify the uncertainty in the estimated forces that results from measurement noise and wind loads acting on the footbridge.…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…The gain matrices M [k] and K [k] are determined such that the input estimatesp [k|k] and state estimatesx [k|k] are minimum variance and unbiased [24,26]. In the equations above, the system is assumed to be time-invariant.…”

Section: Input Estimatioñmentioning

confidence: 99%

“…This algorithm was introduced to the field of structural dynamics by Lourens et al [25], extending the use of the algorithm to reduced-order models. The algorithm is further extended in [26], for cases where accelerations are measured in the presence of unknown stochastic excitation. A similar approach was proposed by Niu et al [27].…”

Section: Introductionmentioning

confidence: 99%

“…This paper presents a full-scale verification of the joint input-state estimation algorithm proposed in [26] using data obtained from an in situ experiment on a footbridge. The algorithm is used to identify the impact, harmonic, and swept sine excitations applied to the bridge deck.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Verification of joint input-state estimation for force identification by means of in situ measurements on a footbridge

Maes

Nimmen

Lourens

et al. 2016

Mechanical Systems and Signal Processing

Self Cite

View full text Add to dashboard Cite

This paper presents a verification of a joint input-state estimation algorithm using data obtained from in situ experiments on a footbridge. The estimation of the input and the system states is performed in a minimum-variance unbiased way, based on a limited number of response measurements and a system model. A dynamic model of the footbridge is obtained using a detailed finite element model that is updated using a set of experimental modal characteristics. The joint inputstate estimation algorithm is used for the identification of two impact, harmonic, and swept sine forces applied to the bridge deck. In addition to these forces, unknown stochastic forces, such as wind loads, are acting on the structure. These forces, as well as measurement errors, give rise to uncertainty in the estimated forces and system states. Quantification of the uncertainty requires determination of the power spectral density of the unknown stochastic excitation, which is identified from the structural response under ambient loading. The verification involves comparing the estimated forces with the actual, measured forces. Although a good overall agreement is obtained between the estimated and measured forces, modeling errors prohibit a proper distinction between multiple forces applied to the structure for the case of harmonic and swept sine excitation.

show abstract

Section: Mathematical Formulationmentioning

confidence: 99%

Section: Mathematical Formulationmentioning

confidence: 99%

Section: Input Estimatioñmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Verification of joint input-state estimation for force identification by means of in situ measurements on a footbridge

Maes

Nimmen

Lourens

et al. 2016

Mechanical Systems and Signal Processing

Self Cite

View full text Add to dashboard Cite

show abstract

Earthquake input and state estimation for buildings using absolute floor accelerations

Taher

Fang

2020

Earthq Engng Struct Dyn

View full text Add to dashboard Cite

After earthquakes, structural response such as interstory drift is critical for accurate structural assessment for buildings. Typically, direct integration of absolute floor accelerations does not yield reliable floor displacements due to the long‐period drifts caused by noise, a widely acknowledged challenge. In this case, model‐based estimation strategies can be employed, which often require the ground input for better accuracy. However, in many cases the ground input may not be available for lack of instrumentation or even be unmeasurable due to soil‐structure interaction, hence needs to be estimated. Earthquake input estimation in this case is particularly challenging due to the lack of direct feedthrough term, leading to low observability of system input. As a result, input estimation is sensitive to modeling error, measurement noise, and incomplete measurements. To address this challenge, a hybrid strategy is proposed to estimate earthquake input, states, and acceleration response at unmeasured floors using limited absolute floor acceleration measurements. First, the earthquake input is estimated through a maximum a posteriori (MAP) estimation method, and then the estimated input is combined with Kalman filter to further estimate states and unmeasured responses. A comprehensive assessment was performed through a series of numerical and experimental tests including a comparative study with a popular online model‐based method. While the online method demonstrated certain sensitivity to modeling error and measurement noise due to weak observability, the proposed strategy showed robustness and accuracy under realistic and challenging conditions. Further verification is also performed using a real‐world building structure that experienced earthquake events.

show abstract

Estimation of maximum drift of multi‐degree‐of‐freedom shear structures with unknown parameters using only one accelerometer

Mita

2021

Structural Contr & Hlth

View full text Add to dashboard Cite

Summary When a multi‐degree‐of‐freedom (MDOF) shear structure is excited by seismic excitation, the connections between structural and non‐structural members may become loose or slight structural damage may arise, which cause the natural frequencies identified from the healthy structure shift. However, it is not easy to accurately re‐identify the natural frequencies from the response recorded by one sensor. This paper presents a method to estimate the maximum inter‐story drift and time histories of the relative displacement of all stories of the structure from the measured absolute response. First, the absolute acceleration and relative displacement are formulated in modal coordinates, and a state‐space expression is derived. Then, a scheme to reduce the modeling error arising from shifts in the structural frequencies is devised that uses the genetic algorithm (GA) and a reasonably chosen fitness function. The applicability of this approach was investigated by conducting numerical simulations focusing on the rate of change in natural frequencies and selection of the lower bound of GA variables. Further simulations were conducted to investigate the robustness, installation location, and truncation error of the proposed method. Finally, the proposed approach was validated in a simple experiment. The results indicate that it can accurately estimate the time histories of the relative displacement and maximum inter‐story drifts of all floors in the case of a significant change in natural frequencies and a large search range of GA variables. In addition, it is robust against environmental noise and performs well even when the model includes only lower modal responses.

show abstract

Joint input-state estimation in structural dynamics

Cited by 110 publications

References 16 publications

Verification of joint input-state estimation for force identification by means of in situ measurements on a footbridge

Verification of joint input-state estimation for force identification by means of in situ measurements on a footbridge

Earthquake input and state estimation for buildings using absolute floor accelerations

Estimation of maximum drift of multi‐degree‐of‐freedom shear structures with unknown parameters using only one accelerometer

Contact Info

Product

Resources

About