To prevent accidents caused by collapse and rockfall tunnel faces during construction, we considered vibration monitoring using a millimeter-wave (78-GHz band) DBF-based high-speed imaging radar. Basic performance tests were conducted in a radio anechoic room and test facility simulating an actual tunnel. It was confirmed that the accuracy of the 0.1-mm displacement-measurement, high-speed sampling of 0.001 s, and individual movements of several targets could be distinguished. Based on the basic test results, on-site measurements were performed at an actual tunnel construction site. The displacement and vibration changes of a tunnel face at the time of breakthrough can be captured; in addition, large velocity changes occur in a working face before breakthrough, and it might be possible to detect an abnormal tunnel face in advance. In addition, it was confirmed that the movement of the rockfall location was almost precisely captured even for small-scale flaking during the drilling of the working face, regardless of the condition in which a part of the measurement range became shadowed.
The authors have developed a digital beam forming dynamic imaging radar system, ”VirA.” It is a cutting-edge non-contact measurement technology for space-continuous vibration monitoring of buildings. In this research, the authors have presented the vibration monitoring method by conducting vibration measurements of an actual tall building. Experiments were performed to compare the performances of two time-synchronized radars and a conventional vibrometer. Frequency analysis was performed and the dominant frequencies were compared with those determined from the conventional vibrometer.
KEYWORDS: Sensors, Structural health monitoring, Damage detection, Detection and tracking algorithms, Earthquakes, Data modeling, System identification, Modal analysis, Error analysis, Systems engineering
This paper proposes damage detection algorithm of a structural health monitoring (SHM) system for a seismic isolated building. The proposed algorithm consists of the multiple-input multiple-output (MIMO) modal analysis and the physical parameter identification. A story stiffness as a direct damage index of the structure is identified using complex modal properties obtained by subspace-based state space model identification (4SID). This algorithm is tuned for seismic isolated structures using substructure approach (SSA). Of a seismic isolated structure, the isolation layer and superstructure are treated as separate substructures as they are distinctly different in their dynamic properties. The damage scenario for a seismic isolated structure is much simpler and more accurate than for a conventional building. Our strategy is to maximize the benefit of this simplicity. The effectiveness is verified through the numerical analysis and experiment. The method is finally applied to an existing building in Japan. The monitoring target is a 7-story seismic isolated building with the gross floor area of 18606m2 and with total height of 31m. This study shows potential to build a simple and reliable SHM system for seismic isolated buildings.
An example of structural health monitoring system using FBG-based optical fiber sensors for the damage tolerant building structure is presented. The damage tolerant building is equipped with several passive dampers for absorbing earthquake input energy, and the structural health monitoring system is focused to monitor performance of these dampers. FBG-based optical fiber sensor modules are developed to apply in structural health monitoring system for damage tolerant building structures. The system is verified on static measurement and dynamic measurement in earthquake.
A series of FBG sensor modules for the building structure are developed. And the health monitoring system using FBG-based sensor modules were installed. Which was used for the 12th floor steel frame building of the damage tolerant built. There are 64 FBG-based sensors in the building structure. A detailed experiment was done about the FBG-based displacement sensor module, the FBG-based strain sensor module, and the FBG-based temperature modules.
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