AI・データサイエンス論文集
Online ISSN : 2435-9262
DISPLACEMENT ESTIMATION OF NONLINEAR SDOF SYSTEM UNDER SEISMIC EXCITATION USING KALMAN FILTER FOR STATE-PARAMETER ESTIMATION
Yaohua YANGTomonori NAGAYAMADi SU
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ジャーナル オープンアクセス

2020 年 1 巻 1 号 p. 1-10

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An extended Kalman filter (EKF) based displacement estimation method for nonlinear SDOF systems under seismic excitation is proposed. In this method, time intervals where the system experiences significant nonlinearity or not are firstly distinguished. For a time period when the system is in an elastic phase, available observations for EKF are acceleration, displacement obtained via double integration of acceleration, and residual displacement. During a time period with significant nonlinearity, acceleration and virtual displacement measurement are employed as observations, and the displacement is estimated along with time-variant stiffness using an augmented state vector in EKF. The results are further smoothed by extended Kalman smoother (EKS). The proposed method is studied on an SDOF system with a bi-linear hysteresis model in detail and further verified considering various hysteresis models and earthquake excitations. The estimated displacements are shown to be accurate.

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© 2020 Japan Society of Civil Engineers
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