A New Shape Sensing Approach for Multilayer Composites Beams With Variable Cross‐Section Under Nonlinear Deformations

Composite materials are widely used in engineering structures such as aircraft, wind turbine blades, and bridges because of their light weight, high strength, and fatigue resistance. Owing to their use in complex working environments and heavy load conditions, these multilayer composite variable‐section structures are very prone to geometric nonlinear deformations, which can affect their working performance and even lead to damage. Shape sensing is an effective approach for monitoring the deformation of these composite structures in practical applications. However, existing shape sensing methods are not capable of simultaneously addressing geometric nonlinearity, variable cross‐section effects, and multilayer composite coupling, which are essential for accurate reconstruction of practical large‐scale structures. Therefore, this paper proposed a new method—the rotation angle approximation (RAA) algorithm for shape sensing applications. This method can calculate the axial angle by constructing a least‐squares error functional between the theoretical and actual curvatures, thereby reconstructing the deformed shape of the multilayer composite variable‐section beam. The accuracy and feasibility of the method are validated through numerical simulations. Specifically, a high‐fidelity 16‐MW wind turbine blade model was built. The shear web, a representative multilayer composite beam with variable cross‐section, was selected to further demonstrate the algorithm's capability in reconstructing large deformations of complex real‐world structures. The results show that the RAA can accurately predict the deformed shapes of multilayer composite variable‐section beams.