Parameter estimation of a cantilever beam model typically involves estimating the effective parameters of the system for an assumed mode shape. This shape assumption, which is difficult to verify with traditional single-point sensors, can be validated through the distributed strain measurements available from optical Fiber Bragg Grating sensors. In this paper, the experimental mode shapes of a cantilever beam acquired from Fiber Bragg Grating sensors are compared with the analytical predictions of classical beam theory for the first two bending modes. A single degree of freedom model is also analyzed for the first bending mode and compared to the distributed parameter model and experimental data. It is shown that the distributed parameter model provides a good estimate of the strain profile at the first two natural frequencies, and that the single degree of freedom and distributed parameter models are in close agreement at the first natural frequency.
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ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
September 18–20, 2017
Snowbird, Utah, USA
Conference Sponsors:
- Aerospace Division
ISBN:
978-0-7918-5826-4
PROCEEDINGS PAPER
Experimental Mode Shape Identification for a Cantilever Beam Using Optical Fiber Bragg Gratings
Patrick S. Heaney,
Patrick S. Heaney
Old Dominion University, Norfolk, VA
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Onur Bilgen
Onur Bilgen
Rutgers University, Piscataway, NJ
Search for other works by this author on:
Patrick S. Heaney
Old Dominion University, Norfolk, VA
Onur Bilgen
Rutgers University, Piscataway, NJ
Paper No:
SMASIS2017-3736, V002T04A003; 7 pages
Published Online:
November 9, 2017
Citation
Heaney, PS, & Bilgen, O. "Experimental Mode Shape Identification for a Cantilever Beam Using Optical Fiber Bragg Gratings." Proceedings of the ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 2: Modeling, Simulation and Control of Adaptive Systems; Integrated System Design and Implementation; Structural Health Monitoring. Snowbird, Utah, USA. September 18–20, 2017. V002T04A003. ASME. https://doi.org/10.1115/SMASIS2017-3736
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