Paper
1 April 2016 Optimized sensor location for estimating story-drift angle for tall buildings subject to earthquakes
Author Affiliations +
Abstract
Structural Health Monitoring (SHM) is a technology that can evaluate the extent of the deterioration or the damage of the building quantitatively. Most SHM systems utilize only a few sensors and the sensors are placed equally including the roof. However, the location of the sensors has not been verified. Therefore, in this study, the optimal location of the sensors is studied for estimating the inter-story drift angle which is used in immediate diagnosis after an earthquake. This study proposes a practical optimal sensor location method after testing all the possible sensor location combinations. From the simulation results of all location patterns, it was proved that placing the sensor on the roof is not always optimal. This result is practically useful as it is difficult to place the sensor on the roof in most cases. Modal Assurance Criterion (MAC) is one of the practical optimal sensor location methods. I proposed MASS Modal Assurance Criterion (MAC*) which incorporate the mass matrix of the building into the MAC. Either the mass matrix or the stiffness matrix needs to be considered for the orthogonality of the mode vectors, normal MAC does not consider this condition. The location of sensors determined by MAC* was superior to the previous method, MAC. In this study, an important knowledge of the location of sensors was provided for implementing SHM systems.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sayuki Ozawa and Akira Mita "Optimized sensor location for estimating story-drift angle for tall buildings subject to earthquakes", Proc. SPIE 9805, Health Monitoring of Structural and Biological Systems 2016, 98052P (1 April 2016); https://doi.org/10.1117/12.2218822
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CITATIONS
Cited by 4 patents.
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KEYWORDS
Sensors

Earthquakes

Buildings

Structural health monitoring

Near field

Data modeling

Electroluminescence

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