Computational Studies of a Strain-Based Deformation Shape Prediction Algorithm for Control and Monitoring Applications

A modal approach is investigated for real-time deformation shape prediction of lightweight unmanned flying aerospace structures, for the purposes of Structural Health Monitoring (SHM) and condition assessment. The deformation prediction algorithm depends on the modal properties of the structure and uses high-resolution fiber-optic sensors to obtain strain data from a representative aerospace structure (e.g., flying wing) in order to predict the associated real-time deflection shape. The method is based on the use of fiber-optic sensors such as optical Fiber Bragg Gratings (FBGs) which are known for their accuracy and light weight. In this study, the modal method is examined through computational models involving Finite-Element Analysis (FEA). Furthermore, sensitivity analyses are performed to investigate the effects of several external factors such as sensor locations and noise pollution on the performance of the algorithm. This work analyzes the numerous complications and difficulties that might potentially arise from combining the state-of-the-art advancements in sensing technology, deformation shape prediction, and structural health monitoring, to achieve a robust way of monitoring ultra lightweight flying wings or next-generation commercial airplanes.