Model-Based Inspection Planning for Large-Scale Structures Using Unmanned Aerial Vehicles

This chapter proposes a model-based inspection planning framework for damage diagnostics and maintenance optimization of large-scale deteriorating structures. An objective function is constructed using the definition of cost per unit time (CPUT) based on the three key parameters of unmanned aerial vehicle (UAV) inspection: inspection distance, inspection interval, and crack limit for repair action. To accelerate the process of optimizing the expensive-to-evaluate function, a Bayesian optimization is employed which improves the time and computational efficiency. The results demonstrate that the proposed method is able to efficiently determine the optimal parameters of UAV inspection parameters and continuously update the information model.