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Automated Assessment of Building Damage from Seismic Events Using Smartphones
This paper addresses automated reconnaissance of building damage from seismic events using smartphones. Damage assessment is enabled by computation of interstory drift ratios (IDR) and comparison of those ratios with known damage limits. Through this process, it is possible to electronically tag buildings in terms of their level of damage right after a seismic event. To illustrate this idea, this paper presents a process for estimating IDR at each floor. The premise is that each floor has a number of smartphones providing records of the acceleration response. The proposed method addresses noise reduction, sliding detection, data fusion, and double integration errors. Shake table testing is conducted to demonstrate and validate the proposed process. The experimental variables include number of smartphones and smartphone type, and hence noise associated with the measured signal, and friction coefficient of the shells used to protect the phones. It is shown that multiple smartphone records need to be aggregated to reduce stochastic errors but the presence of amplitude dependent scale factor errors in current smartphone technology limit the value of using too many devices. These limitations are expected to be alleviated as the quality of smartphone accelerometers improves in the future.
Automated Assessment of Building Damage from Seismic Events Using Smartphones
This paper addresses automated reconnaissance of building damage from seismic events using smartphones. Damage assessment is enabled by computation of interstory drift ratios (IDR) and comparison of those ratios with known damage limits. Through this process, it is possible to electronically tag buildings in terms of their level of damage right after a seismic event. To illustrate this idea, this paper presents a process for estimating IDR at each floor. The premise is that each floor has a number of smartphones providing records of the acceleration response. The proposed method addresses noise reduction, sliding detection, data fusion, and double integration errors. Shake table testing is conducted to demonstrate and validate the proposed process. The experimental variables include number of smartphones and smartphone type, and hence noise associated with the measured signal, and friction coefficient of the shells used to protect the phones. It is shown that multiple smartphone records need to be aggregated to reduce stochastic errors but the presence of amplitude dependent scale factor errors in current smartphone technology limit the value of using too many devices. These limitations are expected to be alleviated as the quality of smartphone accelerometers improves in the future.
Automated Assessment of Building Damage from Seismic Events Using Smartphones
Na, Yunsu (Autor:in) / El-Tawil, Sherif (Autor:in) / Ibrahim, Ahmed (Autor:in) / Eltawil, Ahmed (Autor:in)
10.03.2020
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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