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Conference Paper X-ray image-based flight path planning model of UAVs for non-destructive inspection of wind blades
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Authors
Jungi Lee, HyunYong Lee, Nac-Woo Kim, Yu-Min Hwang, Seok-Kap Ko
Issue Date
2023-06
Citation
International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) 2023, pp.1582-1585
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ITC-CSCC58803.2023.10212472
Abstract
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.
KSP Keywords
Flight Path Planning, Image-based, Learning model, Model tracking, Non-Destructive Inspection, Planning Model, Wind blade, X-ray Generator, deep learning(DL), training set, wind turbine blades