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Published on: May 23, 2017
Large Structural Shear Deformation and Failure Monitoring Using Bend Losses in Polymer Optical Fibre
Terry Y P Yuen1, Cheng-An Tsai1, Trissa Deb1
1Department of Civil Engineering, National Chiao Tung University, Hsinchu 30010, Taiwan.
This study introduces a new method using distributed optical fibre sensing (DOFS) to detect structural shear deformation. The technique accurately locates damage and measures its magnitude, aiding post-disaster assessments.
Area of Science:
- Structural Engineering
- Sensing Technologies
- Materials Science
Background:
- Structural instability often results from large shear deformation, necessitating precise damage detection methods.
- Distributed optical fibre sensing (DOFS) offers continuous monitoring superior to point-based sensors for structural health assessment.
Purpose of the Study:
- To develop a novel measurement theory and algorithm for evaluating structural shear deflection using DOFS.
- To assess the efficacy of photon-counting Optical Time Domain Reflectometer (ν-OTDR) with polymer optical fibres (POFs) for shear deformation monitoring.
Main Methods:
- Development of a new theory integrating large beam deflection and optical bend loss.
- Utilisation of a photon-counting ν-OTDR system with POFs for high spatial resolution and large deformation range.
- Experimental validation on concrete beam specimens to monitor rupture failure.
Main Results:
- Successful detection and evaluation of shear deformation events.
- Accurate determination of event locations and magnitudes for normalized shear deformation > 0.2.
- Location error < 0.5 m for smaller deformations; multiple events detectable if separated by > 5 m.
- POF configuration maximizing curvature at failure yielded strongest signals.
Conclusions:
- The proposed DOFS technique effectively identifies and quantifies structural shear deformation and failure.
- The system demonstrates potential for real-time structural health monitoring and post-disaster rapid assessment.
- Optimized POF configurations enhance signal detection for rupture monitoring.
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