Buckling detection and shape reconstruction using strain distributions measured from a distributed fiber optic sensor

This paper proposes to detect buckling and reconstruct three-dimensional deformations using distributed fiber optic sensors. The distributed sensors measured strain distributions with sub-millimeter resolutions based on optical frequency domain reflectometry in real time. Buckling was detected from high-resolution strain distributions measured from specimens. An effective and practical shape reconstruction approach was developed to derive nonsymmetrical deformations based on the strain distributions. The reconstructed shape was validated using a computer vision method that measured point cloud from the specimens. A parametric study was conducted to investigate the effects of the key sensing parameters such as the spatial resolution and sensor deployment scheme on the performance of the shape reconstruction approach, and used to optimize the resolution and deployment of distributed sensors. This research will advance the capability of buckling detection and shape reconstruction through distributed sensing for engineering structures under complex loading conditions.