Improved deformation reconstruction of composite material structures based on optical fiber sensing.

Abstract

Due to high strength and lightweight, composite material structures have been widely used in various industries such as aerospace, automotive, civil engineering, and healthcare. Real-time deformation monitoring based on optical fiber sensing technology holds immense potential in composite materials' structural health monitoring (SHM). In this study, structural deformation reconstruction algorithms have been investigated by improving the slope recursion algorithm and the Ko displacement theory. The slope recursion algorithm is enhanced through angle averaging. Cross-validation is employed to increase strain-fitting accuracy for the Ko displacement theory. Finite element simulation analysis and deformation reconstruction experiments of a carbon fiber composite plate were conducted to validate the deformation reconstruction algorithms. Fiber Bragg grating (FBG) sensors were applied to measure quasi-distributed strain as inputs for the algorithms. The results show that the overall reconstruction accuracy increased by 1.91% with the improved slope method and by 0.92% with the optimized Ko displacement theory. Deformation reconstruction experiments of a composite material reinforced structure were carried out, and 70 FBG sensors were installed on its surface for strain field measurement. The experimental results indicate the feasibility of the proposed deformation reconstruction methods for complex structures.