Buckling detection and shape reconstruction using strain distributions measured from a distributed fiber optic sensor. (15th August 2022)

• Record Type: Journal Article
• Authors: Tan, Xiao; Guo, Pengwei; Zou, Xingxing; Bao, Yi
• Is Part Of: Measurement. Volume 200(2022)
• Publication Date: 2022-08-15
• Subjects: Buckling -- Distributed fiber optic sensors -- Optical frequency domain reflectometry -- Shape reconstruction -- Structural health monitoring -- Thin-walled structures; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2022.111625
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: Distributed fiber optic sensors are used to detect buckling for thin-walled structures. An effective and practical method is developed for shape reconstruction using strain fields. Strain fields due to buckling are measured by fully distributed sensors with sub-mm resolution. The proposed shape reconstruction method is compared with a computer-vision method. Effects of spatial resolution and sensor deployment on shape reconstruction are discussed. Abstract: 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.