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- 2019 (33) (entfernen)
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- 8.6 Faseroptische Sensorik (33) (entfernen)
Eingeladener Vortrag
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In the present study, the impact of static traffic loading on the slight deflection effects in the concrete structure of an existing bridge has been investigated using distributed fiber optic sensors. In the face of increasing traffic density and severe traffic loading, the results of the load tests on the Amsterdam bridge 705 make an important contribution to the understanding of its structural behavior. The concept of the static loading was based on the use of two 36-ton trucks stopped on the bridge at multiple pre-determined locations. The load applied in this way led to location-dependent small deflection effects recorded as longitudinal strain of the sensing fiber embedded at the underside of the bridge. The measurements were performed with a commercially-available solution based on Tunable Wavelength Coherent Optical Time Domain Reflectometry with the measurement accuracy in the range of 0.5 µm/m.
Wavelength-scanning distributed acoustic sensing for structural monitoring and seismic applications
(2019)
We introduce wavelength-scanning coherent optical time domain reflectometry (WS-COTDR) for dynamic vibration sensing along optical fibers. The method is based on spectral shift computation from Rayleigh backscatter spectra. Artificial neural networks (ANNs) are used for fast and high-resolution strain computation from raw measurement data. The applicability of the method is demonstrated for vibration monitoring of a reinforced concrete bridge. We demonstrate another application example for quasi-static and dynamic measurement of ground deformation and surface wave propagation along a dark fiber in a telecommunication cable.
Wavelength-scanning distributed acoustic sensing for structural monitoring and seismic applications
(2019)
We introduce wavelength-scanning coherent optical time domain reflectometry (WS-COTDR) for dynamic vibration sensing along optical fibers. The method is based on spectral shift computation from Rayleigh backscatter spectra. Artificial neural networks (ANNs) are used for fast and high-resolution strain computation from raw measurement data. The applicability of the method is demonstrated for vibration monitoring of a reinforced concrete bridge. We demonstrate another application example for quasi-static and dynamic measurement of ground deformation and surface wave propagation along a dark fiber in a telecommunication cable.