Abstract
Recently damage detection methods based on measured vibration data for structural health monitoring (SHM) have been intensively studied. In order to decrease the number of required sensors, however, most of their methods focus only on single dimensional systems, in spite that there are some cases that torsional vibration greatly affect for structural damage. Although some studies consider multiple dimensional systems using frame structures, usually they need lots of sensors and calculation is time-consuming. Therefore, the balance between the cost and the particularity is very important for SHM system. In this paper, a method to localize the damaged area of multi-story buildings considering torsional components is proposed to detect the damage simply and particularly. This method focuses on shift in the center of rigidity caused by induced damage. The damaged quadrant of a certain story is identified comparing story eccentric distances of before and after damage-inducing seismic events. An adaptive extended Kalman filter (AEKF) is utilized to identify unknown structural parameters. Using a model which has four columns in each floor, several cases are considered in the verification study to disclose the capability of our proposed method.
Original language | English |
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Title of host publication | Proceedings of SPIE - The International Society for Optical Engineering |
Publisher | SPIE |
Volume | 9437 |
ISBN (Print) | 9781628415407 |
DOIs | |
Publication status | Published - 2015 |
Event | Structural Health Monitoring and Inspection of Advanced Materials, Aerospace, and Civil Infrastructure 2015 - San Diego, United States Duration: 2015 Mar 9 → 2015 Mar 12 |
Other
Other | Structural Health Monitoring and Inspection of Advanced Materials, Aerospace, and Civil Infrastructure 2015 |
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Country/Territory | United States |
City | San Diego |
Period | 15/3/9 → 15/3/12 |
Keywords
- Damage Detection
- Eccentricity
- Extended Kalman Filter
- Structural Health Monitoring
- Torsional Vibration
ASJC Scopus subject areas
- Applied Mathematics
- Computer Science Applications
- Electrical and Electronic Engineering
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics