Our laboratory has been working on developing a practical structural health monitoring (SHM) system consisting of digital sensor network and a cloud server. The usefulness of such a system has been recognized by real estate companies, construction companies and design firms. We estimate the number of systems exceeded one hundred. In the SHM system, modal parameters such as natural frequency and damping ratio are important damage indicators to diagnose the condition of structures. However, existing conventional methods require the knowledge of expert to select the proper modal parameters. This is the barrier for promoting the system. Under an emergency event, we will not be able to have immediate help from the experts as they will be very busy to take care of so many buildings. In this paper, we propose an automatic estimation method to extract fundamental modal frequencies and damping ratios under the assumption we have information on mass distribution and mode shapes. We use these information to filter out the necessary modal information only so that any system identification methods that are applicable to single-degree-of-freedom systems will work well. To test the method, 40 story steel and RC building structural models were developed. They were simplified to tri-linear skeleton type nonlinear model to show the feasibility of the proposed method to nonlinear level as well. Finally, the method is applied to real tall buildings near Shinjuku Station. The building is 29 story and made of steel. It suffered nonstructural damage during Tohoku Earthquake of March 11, 2011.
|出版ステータス||Published - 2017|
|イベント||6th Asia Pacific Workshop on Structural Health Monitoring, APWSHM 2016 - Hobart, Australia|
継続期間: 2016 12 7 → 2016 12 9
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