Application of Story-Wise Shear Building Identification Method to Actual Ambient Vibration

Takewaki

2016

Self Cite

In order to identify physical model parameters of a high-rise building, a new story stiffness identification method is presented based on a shear-bending model and the identification function. Although a shear building model may be the simplest conventional model for representing tall buildings, the system identification (SI) method using that model is not necessarily appropriate. This is because the influence of bending deformation is predominant in such high-rise buildings. For this reason, a shear-bending model is used where the shear and bending stiffnesses are unknown. In the previous researches using the shear-bending model, it was difficult to identify the bending stiffnesses stably and reliably. In this paper, to overcome such instability of bending stiffness identification of the shear-bending model, a new SI algorithm using both the shear model and the shearbending model is presented. The proposed SI algorithm is based on the observation that the fundamental-mode shape of the identified shear model is similar to that of the shear-bending model identified in the previous SI method. In order to verify the advanced SI method, two different 20-story building models are investigated in the numerical simulations. From the results of the simulations, both the shear and bending stiffnesses of the shear-bending model are identified reliably and stably in the proposed SI method.

Section: Discussionmentioning

confidence: 99%

Advanced System Identification for High-Rise Building Using Shear-Bending Model

Takewaki

2016

Self Cite

“…used as the base input. These micro-tremors data were obtained at Disaster Prevention Research Institute of Kyoto University, Japan (Fujita et al, 2015). In following numerical examples, the bandlimited white noise is added to the output data as the measurement noise, i.e., horizontal and rotational accelerations, independently at each story.…”

Section: Numerical Examplesmentioning

confidence: 99%

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

Takewaki

2018

Self Cite

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.

“…On the other hand, Nakamura (2000, 2005) developed a unique SI concept which is originally from the work by Udwadia et al (1978) for a shear building model (S model). Although the SI method by Nakamura (2000, 2005) was innovative, an additional effort should be provided in applying to actual data represented by micro-tremors (Ikeda et al, 2014;Fujita et al, 2015;Koyama et al, 2015). This may result from the small signal/noise (SN) ratio especially in the low frequency range.…”

Section: Introductionmentioning

confidence: 99%

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

Shintani

Yoshitomi

et al. 2019

Self Cite

In most building structures, floors with sufficient in-plane stiffness exist and an assumption of rigid in-plane stiffness is valid. However, in some building structures, an assumption of rigid in-plane stiffness does not hold. A method of system identification (SI) for physical parameters (stiffness, damping) is proposed for three-dimensional (3D) building structures with in-plane flexible floors. The stiffness and damping parameters of each vertical structural frame in the 3D building structure are identified from the measured floor horizontal accelerations together with the stiffness and damping parameters of each floor. It is shown that a batch processing least-squares estimation method for many discrete time-domain measured data enables the direct identification of both the stiffness and damping parameters of each vertical structural frame and the stiffness and damping parameters of each floor. The proposed method possesses an advantage that all stiffness and damping parameters of vertical frames and horizontal frames (floors) can be identified simultaneously without search iteration. The accuracy and reliability of the proposed method are made clear by numerical simulations for measured data without noise and measured data with noise. A method of noise elimination is proposed to enhance the identification accuracy. Finally, experiments using a shaking table are conducted for the accuracy investigation of the proposed identification method. It is confirmed that the proposed identification method possesses a reliable ability to identify the stiffness and damping parameters for 3D building structures with in-plane flexible floors.