Computer-aided feature recognition of CFRP plates based on real-time strain fields reflected from FBG measured signals

Condition monitoring of critical and expensive carbon fiber reinforced polymer (CFRP) composite infrastructures is extremely essential task for uninterrupted operation and the durability of structures. Therefore, accurate and robust monitoring techniques and correlated damage identification algorithms need to be developed to characterize the health status of the CFRP structures. However, the effectiveness of existing methods is highly dependent on the structural properties of the CFRP plates. To identify the random damages caused by static or dynamic forces, the concept to establish the real-time strain fields of the structures based on measured signals is proposed. A moving surface spline interpolation algorithm based on Green's function has been developed to map the real-time strain fields of the CFRP plate using strain measured by surface-attached FBG sensors. A few static and impact loadings have been applied to a sample CFRP plate and the strain-field prediction by the proposed algorithm has been evaluated by a finite element model. Time and frequency domain analysis has also been conducted to recognize the dynamic response of the CFRP plates. Results indicate that the proposed algorithm can establish real-time strain field predictions with high precision, which can be used to recognize the static and dynamic responses of CFRP plate. Most importantly, the method is independent on the structural properties of the plate and the sensor layout, which is particularly significant for constructing the smart health monitoring system of CFRP.