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

Area of Science:

• Materials Science
• Mechanical Engineering
• Structural Health Monitoring

Background:

• Composite materials offer high strength and low weight, leading to widespread industrial adoption.
• Optical fiber sensing technology is crucial for real-time structural health monitoring (SHM) of composites.
• Accurate deformation reconstruction is vital for assessing the integrity of composite structures.

Purpose of the Study:

• To investigate and improve structural deformation reconstruction algorithms for composite materials.
• To enhance the accuracy and feasibility of real-time SHM using optical fiber sensing.
• To validate improved algorithms through simulations and experiments on composite structures.

Main Methods:

• Enhancement of the slope recursion algorithm via angle averaging.
• Optimization of the Ko displacement theory using cross-validation for strain-fitting accuracy.
• Finite element simulation and experimental validation using Fiber Bragg Grating (FBG) sensors for strain measurement.

Main Results:

• The improved slope method increased overall reconstruction accuracy by 1.91%.
• The optimized Ko displacement theory improved accuracy by 0.92%.
• Experiments on a composite material reinforced structure with 70 FBG sensors demonstrated the methods' feasibility.

Conclusions:

• The developed algorithms significantly improve the accuracy of structural deformation reconstruction.
• The enhanced methods are feasible for real-time SHM of complex composite structures.
• Optical fiber sensing combined with improved algorithms offers a robust solution for composite structural integrity assessment.