Optimal FBG Sensor Layout Assessment for Accurate Structural Feature Recognition of Composite Plates

Carbon fiber-reinforced polymer (CFRP) composites are increasingly used in aerospace, rail transportation, and energy engineering owing to their high specific strength and corrosion resistance. However, their complex and interacting damage mechanisms, including delamination and matrix cracking, present significant challenges for reliable structural health monitoring. Fiber Bragg grating (FBG) sensors offer distinct advantages for monitoring composite structures because of their compact size, immunity to electromagnetic interference, embeddability, and capability for distributed strain measurement. Nevertheless, the effectiveness of an FBG sensing network depends strongly on the spatial distribution of the sensing points. This study proposes a finite-element-assisted framework for evaluating and improving FBG sensor layouts for strain-field reconstruction and structural feature characterization of composite plates. The framework first reconstructs the spatial strain field from limited sensing data using interpolation and least-squares fitting methods, and then evaluates the performance of existing and candidate sensor layouts based on reconstruction errors and spatial coverage of structurally important regions. A strain-gradient-informed heuristic strategy is subsequently developed to improve sensor placement by combining high-gradient region identification, spatially uniform coverage, minimum-distance constraints, and predefined support-region monitoring requirements. The Fourier least-squares fitting method provides the lowest reconstruction error among the investigated approaches and is therefore adopted for subsequent layout evaluation and improvement. Finite-element simulations and experimental measurements are used to assess the reconstruction performance and identify the advantages and limitations of different sensor layouts under static and dynamic loading conditions. The results demonstrate that the proposed framework can effectively evaluate existing FBG layouts and provide a systematic basis for their improvement, while also revealing the trade-off between local strain-gradient resolution and global spatial coverage. The proposed framework provides practical guidance for the performance-oriented design and improvement of FBG sensor networks for structural health monitoring of composite structures.