X-Ray Image-Based Flight Path Planning Model of UAVs for Non-Destructive Inspection of Wind Blades

In this paper, we suggest a method for the flight path planning of UAVs equipped with X-ray generator and detector to develop a non-destructive inspection solution that detects defects inside wind turbine blades. To implement it, X-ray images of the inside of the wind blade are acquired and used as a training set for a deep learning model through augmentation of the X-ray image. Through this deep learning model, the implementation of the deep learning model tracking the lightning cable inside the wind blade, and determines UAV's flight direction.