Stiffness Identification of High-Rise Buildings Based on Statistical Model-Updating Approach

Abstract

A system identification problem is investigated for high-rise buildings to identify the story stiffnesses of a shear-bending model (SB model). In the previously proposed stiffness identification method due to the present authors, the shear and bending stiffnesses of the SB model were identified by means of the subspace and inverse-mode methods. The lowest mode of horizontal displacements and floor rotation angles of the objective building was identified first by using measured data of both horizontal and rotational accelerations via the subspace method. Taking into account the resolution in the measurement of floor rotation angles in lower stories, floor rotation angles in all stories were predicted from the floor rotation angle at the top floor. However, it was difficult to obtain the bending stiffnesses reliably in the previous method. In this paper, to overcome the difficulty in the stiffness identification method using the SB model, a statistical model-updating approach is proposed, where the probability distribution of floor rotation angles in the lowest mode is obtained for the identified SB model, and a conditional probability problem is applied by providing additional measured data on floor rotation angle. The proposed stiffness identification method is useful for the structural health monitoring of high-rise buildings. For investigation of the validity of the proposed stiffness identification method, a 10-story plane-building frame is examined under micro-tremor.

Evaluation of stiffness and damping of a base-isolated building considering higher-order modes

“…To solve this problem, methods of estimating the health of building for all stories have been proposed using few acceleration sensor responses (e.g., Shinagawa and Mita, 2013;Suzuki and Mita, 2016;Shirzad-Ghaleroudkhani et al, 2017;Jabini et al, 2018). Moreover, Fujita and Takewaki (2018) proposed a method of estimating the responses of all stories based on nonsimultaneous observations of each floor by moving the measurement device. In such methods, the vibration mode response or participation functions of all the stories must be estimated in advance.…”

Model-Free Identification of Hysteretic Restoring-Force Characteristic of Multi-Plane and Multi-Story Frame Model With In-Plane Flexible Floor

“…Investigations on identification of hysteretic restoring-force characteristics of structures have been conducted in the last four decades (Toussi and Yao, 1983;Cifuentes, 1984;Leontaritis and Billings, 1985;Masri et al, 1987Masri et al, , 1993Loh and Chung, 1993;Kitada, 1998Kitada, , 2000Kitada et al, 2000;Li et al, 2004a,b;Saadat et al, 2004;Zhang and Sato, 2006;Ikhouance and Rodellar, 2007;Tasbihgoo et al, 2007;Worden and Manson, 2010;Brewick et al, 2016;Pelliciari et al, 2018). Although these investigations are versatile, the problem of physical parameter system identification of 3D building structures with mass and/or stiffness eccentricity is a tough problem (e.g., Omrani et al, 2012;Nabeshima and Takewaki, 2017;Shintani et al, 2017Shintani et al, , 2019Fujita and Takewaki, 2018). Compared to the previous researches using neural networks (Saadat et al, 2004;Tasbihgoo et al, 2007;Brewick et al, 2016), wavelet transforms (Kitada, 1998(Kitada, , 2000Saadat et al, 2004), support vector regressions (Zhang and Sato, 2006), fast Bayesian bootstrap filter (Li et al, 2004b), multi-stage iterative approach (Li et al, 2004a), the present approach is suitable for vertical and horizontal framewise simultaneous identification of hysteretic restoring-force characteristics of structural frames with flexible floors within a small amount of computational load.…”

Stiffness and Damping Identification for Asymmetric Building Frame With In-plane Flexible Floors

“…There exists a very limited number of researches on physical-parameter system identification of 3D building structures with eccentricity (for example Omrani et al, 2012;Nabeshima and Takewaki, 2017;Shintani et al, 2017;Fujita and Takewaki, 2018). The existence of many parameters to be identified in 3D building structures may be one reason for difficulty.…”